See also: Related OurFood News
Nutrigenomics is the characterization and sequencing of an
organism's genome and analysis of the relationship between gene activity and
cell function Nutritional genomics, or food genomics is the specific
application of genomics in research pertaining to agriculture, food
processing and food consumption. It studies how food, genes and lifestyle interact.
Nutrigenomics covers the entire food chain. Agriculture use food genomics to
increase vitality, disease resistance and drought and salt tolerance resulting
in increase of yield, reduced loss during storage and transport, enriched
micronutritions and microorganism producing auxiliary substances and food
The knowledge of biological active components has been developed during the
last ten years being the basis for the development of new functional foods,
looking forward to tailored functional foods and personalized foods.
Genomics researche is arousing hope that food will be adaptable to
individuals' genetic profiles. Genetic susceptibility to disease ranging from
intestinal cancer to food infection. Genomics researche is helping to map
these phenomena and give food advice to the personal genetic constitution.
Consumer will be choosing food on the basis of their own genetic constitution
within ten to twenty-five years. People will have a genetic passport that
allows them to use personalized nutrition, personal food with a preventive
Nutrigenomics is not seen as a product category in itself, but rather as
supporting technology for the development of foods of greater nutritional
value, and of functional foods. 
Jean Baptiste Lamarck developed at the end of
the 18th century a theory which modern biologists rated as nonsense.
Lamarck explained nature as being controlled by three biological laws:
Lamarck lived from 1744 to 1829. He was a French botanist and invertebrate
zoologist. He wrote that acquired characteristics could be inherited to
following generations, even not being genetically encoded. Genetic science
experienced then a recession. It was only in 1865 that George Mendel published
the "Mendel' s Laws" of autosomal inheritance, followed by Charles Darwin with
"The Origin of Species" in 1859. Francis Galton (his cousin) rediscovered Mendel' s laws and is considered to be the father of modern genetics.
- Environmental influence on organ development.
- Change in Body structure based on use and disuse of parts.
- Inheritance of acquired characteristics
James Watson and Francis Crick discovered the DNA in 1940's. The Human
Genome Project begun in 1990.
Through informatics driven metabolomic analysis it is possible to identify and
predict the impact of diet on the health of individuals with different
Uses of food genomics
Mei Wang and colleagues 2005 define metabolomics as a concept of systems biology,
enabling the study of living systems from a holistic perspective based
on the profiling of a multitude of biochemical components. The authors stress
that it is useful to study natural products, focusing on the synergetic
effects of components which had not been considered in the study of single
active components. It studies the effect of complex mixtures, such as those
used in Traditional Chinese Medicine, in complex biological systems abridging
it with molecular pharmacology.
Systems biology is a multi-targeted approach which identifies regulatory hubs in complex networks. Systems biology takes the molecular parts (transcripts, proteins and metabolites) of an organism and attempts to fit them into functional networks or models designed to describe and predict the dynamic activities of that organism in different environments. It focuses on complex interactions in biological systems, claiming that it uses a new perspective (holism instead of reduction).
Systems biology explain complex interactions in biological systems 
Systems biology tries to explain properties of a system whose theoretical description is only possible using techniques which fall under the remit of systems biology. These typically involve cell signalling networks, via long-range allostery. Example is given by the authors how the scaffolding proteins NHERF1 and ezrin work in coordination to assemble crucial membrane complexes. 
According to Mochida and Shinozaki 2011 Bioinformatics and several new omics layers such as the interactome, epigenome and hormonome have emerged to explain the molecular systems that underlie various plant functions. Novel applications of neutron spin echo spectroscopy explained allosteric signals by nanoscale protein motion. 
According to Wagner et al. 2011 systems biology can be pursued at three levels: a) the macro-level, or the dynamics of the biological systems of cells, tissues, and organs, as opposed to conventional, static, single-gene or single-protein snapshots of biological processes; b) the micro-level, or biological interactions at the molecular level; and, most importantly, c) the development of methodologies and research tools.  The small molecule inventory (SMI) or metabolome is a pattern of molecules that
reflects the cell's statues. It is the totality of metabolic processes
including anabolism and catabolism. It results from the expression of the
genome and proteome in response to the cellular environment. The metabolome
gives a direct picture of the cells activity and its environment.
The cumulative effects of all expressed and modified proteins represent an
information which is stored in the small molecular inventory (SMI) of the
cell. These molecules include important cellular function compounds, such
as nucleotides, vitamins, antioxidants and catecholamines. This area of
researche is called metabolomics.
When taken in its entirety it is not
always necessary to know the identity of individual components in a metabolic
profile. Systemic changes in pattern are indicative of specific states or of changes in status. This can be measured by quantifying the redox active
components. Detecting and identifying subtle changes can be problematic with
the sensitivity required to identify such molecules. New analytical
technology addresses both problems using the central position of redox
biochemistry in the biological process. 
The general aim of metabolomics is to identify, measure and interpret the
complex time-related concentration, activity and flux of endogenous
metabolites in cells, tissues, and other biosamples such as blood, urine, and
saliva. Metabolites such as small molecules that are the products and
intermediates of metabolism, carbohydrates, peptides, and lipids vary in
concentration, size, structure, polarity, and functional groups. An integrated
set of technologies is needed to address the entire spectrum of
spectrometry can now monitor enzymatic and hormonal regulation of thousands
of metabolites by means of metabolomic techniques. The German Institute of
Human Nutrition (DIFE) in cooperation with the Max-Planck Institute for
molecular Genetics of Plants in Golm/potsdam and Metanomics in Berlin are
adapting a plant analytic system for human tissue and plasma. A specific
metabolite pattern in diabetes patients was possible to be identified. More
detailed knowledge should allow the early identification of unfavorable metabolic profiles in order to develop preventive strategies.
Metabolomics in human blood
Plagemann revives the theory of Jean Baptiste Lamarck quoting that a high
diabetes risk can be passed on to several generations. This is not caused by
a genetic modification, but is due to an acquired condition. Experiments with
rats have demonstrated that diabetes leads to an increased level of insulin in
the unborn. The cells of the brain where the experience of hunger or satiety
are located are irreversibly damaged and the production of insulin excessively
secreted. Diabetes and overwight is therefore programed. .
Martin Pedersen, group leader of a nutrigenomics team of researchers from
Denmark and Japan of Chr Hansen, said that a project analyses the genetic code
of bacteria to improve probiotic food products within the four-year duration of
the project. 
The mother's nutrition can be so important that it can alter her offspring's
susceptibility to disease by changing gene expression, say researchers who
claim to have explained for the first time how maternal nutrition can
predetermine risk of obesity or cancer.
Supplementation during pregnancy
Scientists from Duke University in the US showed they could change the coat
color of baby mice simply by feeding their mothers four common nutritional
supplements before and during pregnancy
Dr Randy Jirtle, senior investigator of the study, published in today's issue of
Molecular and Cellular Biology. "For the first time ever, we have shown precisely
how nutritional supplementation to the mother can permanently alter gene
expression in her offspring without altering the genes themselves."
In experiments, pregnant mice thatreceived vitamin B12, folic acid, choline
and betaine (from sugar beets) gave birth to babies predominantly with brown
coats. In contrast, pregnant mice that did not receive the nutritional
supplements gave birth predominantly to mice with yellow coats. The
non-supplemented mothers were not deficient in these nutrients.
A study of the cellular differences between the groups of baby mice showed
that the extra nutrients reduced the expression of a specific gene, called
Agouti, to cause the coat color change. Yet the Agouti gene itself remained
unchanged. This is called "DNA methylation", and it could potentially affect
dozens of other genes that make humans and animals susceptible to cancer,
obesity, diabetes, and even autism.
During DNA methylation a methyl group attaches to a gene at a specific point
and alters its function. The methyl group silences the gene or reduces its
expression inside a given cell, but does not actually change it. Such an effect
is referred to as "epigenetic"
These changes occur early in embryonic development, before the mother would
even be aware of the pregnancy. According to Dr. Jirtle, any environmental
condition that impacts these windows in early development can result in
developmental changes that are life-long, some of them beneficial and others
detrimental. If such epigenetic alterations occur in the developing sperm or eggs,
Humans and other animals are susceptible to epigenetic changes because of an
evolutionary trait in which "junk" remnants of viral infections, called
"transposons," inserted themselves randomly within the human and animal
genomes. If the transposons have inserted themselves in or near a functional
gene, the gene can be inadvertently methylated, too, thereby reducing its expression.
More than 40 per cent of the human genome is comprised of transposons that are
likely to be methylated, so any genes positioned near them could be at risk for
For example, methylation that occurs near or within a tumour suppressor gene
can silence its anti-cancer activity, said Jirtle. Also they do not know which
of the four nutrients caused methylation of the Agouti gene, revealing the
uncertainty of nutrition's epigenetic effects on cells.
Methylating a single gene can also have multiple effects. For example, as well as
changing coat color, mice that over-express the Agouti protein tend to be obese
and susceptible to diabetes because the protein also binds with a receptor in the
hypothalamus and interferes with the signal to stop eating. Methylating the
Agouti gene in mice, therefore, also reduces their susceptibility to obesity,
diabetes and cancer.
The researchers stressed the importance of understanding the molecular effects
of nutrition on cells, not just the outward manifestations of it.
Dr.Waterland says that diet, nutritional supplements and other seemingly
innocuous compounds can alter the development in utero to such an extent that
it changes the offspring's characteristics for life, and potentially that of
future generations. Nutritional epigenetics could, for example, explain the
differences between genetically identical twins, or the disparities in the
incidence of stroke between the South and the North.
That is the reason why all supplements such as vitamines, minerals probiotics
and a lot of other compounds should be analyzed carefully and nutrition should
be kept as natural as possible.
Berni Canniri et al 2011 explain links among early nutrition, epigenetic processes and diseases in later life, suggesting that maternal and neonatal diet may have long-lasting effects in the development of diseases such as insulin resistance, type 2 diabetes, obesity, dyslipidaemia, hypertension, cardiovascular disease, development and function of gut microbiota. The authors stress the importance of probiotic to restore inadequate gut flora which determine immunity and health status in adult life. The most important butyrate producers appear to be Faecalibacterium prausnitzii and Eubacterium rectale/Roseburia spp.
Influence of gut epigenetic mechanism on immunity and health in adult life 
Dietary fibres influences intestinal microflora composition engaged in the fermentation and production of short chain fatty acids, such as butyrate. In a review in 2012 the group of Berni Cannin found butyrate to be related to the epigenetic regulation of gene expression of anticarcinogenic and chemopreventive effects, anti-inflamatory effects, effects on obesity, insulin resistance, effects on cardiovascular diseases, effects on immune system, effects on inherited disorders and neuroprotective effects. The beneficial activity of butyrate works by inhibiting the histone deacetylase.
Impact of butyrate on epigenetic mechanisms 
Epigenetics focuses on histone acetylation, DNA methylation, and non-coding microRNAs, which are the mechanisms that mold chromatin structures without changing the nucleotide sequence, but are responsible for modifying the expression of critical genes associated with physiologic and pathologic processes. Modulation of histone acetylation and deacetylation through environmental factors, including dietary compounds, may prevent diseases and maintain health. Further studies on butyrate and its its impact on epigenetic mechanisms may improve prevention and treatment of different diseases ranging up to neurological degenerative disorders.
The descendants of plants exposed to stressors, were found by Slaughter et al. 2012 to have a faster and higher accumulation of transcripts of defense-related genes and enhanced disease resistance. Stressors, such as pathogens or treatment with certain chemical compounds can lead to the establishment of a unique primed state of defence which can be transferred to their progeny resulting in an improved protection from pathogens attack as compared to next generations of plants which had not been exposed to the specific stressor.
The offsprings of such transgenerationally primed plants presented an even stronger priming phenotype than their primed parents. 
Stressors, like pathogenic bacteria, may cause changes in DNA methylation patterns altering gene regulation and influencing plant response to stress such as disease resistance.
Dowen et al 2012 describe the role for DNA methylation in regulating the plant immune system. The authors note that the DNA methylomes of plants exposed to bacterial pathogen, avirulent bacteria, or salicylic acid hormone present methylated regions, which up-regulated the 21-nt siRNAs, coupled to transcriptional changes of the transposon and/or the proximal gene. Methylation suppresses the expression of such transposons without changing the DNA sequence.
The authors stress that modifying the DNA methylation patterns of plants may generate pathogen-resistant crops, reduce the use of pesticides and avoid loss of 30 to 40 per cent of crops caused by plant pathogens. It is being suggested to verify whether a similar mechanism may be occurring in human cells.
Pioeterse 2012 explain that acquired stress adaptation can be passed on to a next generation using methylation. The informations concerning the stress condition must be able to withstand mitotic and meiotic divisions. It can persist even when the stress is no longer present. Such epigenetic changes may be changes in DNA methylation patterns, small interfering RNAs (siRNAs) and histone modification which act without changing the DNA sequence. 
According to Luna et al. the immune response to pathogen attack was found to be sustained over one stress-free generation, indicating an epigenetic basis of the phenomenon. The transgenerational systemic acquired resistance is transmitted by hypomethylated genes that direct priming ofsalicylic acid (SA)-inducible defense genes in the following generations. 
Jasmonic acid and related plant metabolites play an important role in the defense signaling cascade in plants under stress. Rasman et al. 2012 report that induced resistance was associated with transgenerational priming of jasmonic acid-dependent defense responses. Arabidopsis mutants that are deficient in jasmonate perception or in the biogenesis of small interfering RNA do not exhibit inherited resistance. 
According to the British biologist Conrad H. Waddington Waddington in 1940, phenotypes are produced by the interplay between genes and their environment. Tarakhovsky comments in 2010 that new understanding of genetics define an epigenetic trait as a stably heritable phenotype resulting from changes in a chromosome without alterations in the DNA sequence. However, epigenetic inheritance that is independent of DNA sequence remains unclear. The durability and temporal limits of epigenetic inheritance must be defined by further research. It must also be cleared if immune phenotypes are influenced by pathogens affecting the epigenome.
Professor John Mattick and colleagues performing the "FANTOM4"
study found that there is a sophisticated network of
regulatory elements that influence the expression of genes of the body. This
opens the understanding on how cells transform from undifferentiated cells to
mature cells with a specific function and explain why some cells turn
cancerous and how stem cells may be used use in regenerative medicine.
Some results of the study are:
Tiny RNAs are 18 nucleotides long, 100 times
smaller than an average gene and are the smallest genetic elements ever
described. According to the authors tiny RNAs are associated with promoters
that switch on genes, and have a role in gene activation, and may be used to
artificially control gene expression.
Transposons are sequences of DNA that can move around to different positions
within the genome of a single cell, a process called transposition. In the
process, they can cause mutations and change the amount of DNA in the genome.
Tiny RNAs 
There are a variety of mobile genetic elements, and they can be grouped based on
their mechanism of transposition. Class I mobile
genetic elements, or retrotransposons, copy themselves by first being transcribed
to RNA, then reverse transcribed back to DNA by reverse transcriptase, and then
being inserted at another position in the genome. Class II mobile genetic elements move
directly from one position to another using a transposase to "cut and paste"
them within the genome.
Transposons were discovered by Barbara McClintock. She wrote that insertions,
deletions, and translocations in the genome could, for example, lead to a change
in the color of corn kernels. About 50% of the total genome of maize consists
of transposons. The Ac/Ds system McClintock described are class II transposons. The maize Ac
(Activator) and Ds (Dissociation) elements comprise a classical two component
transposable element system of the hAT transposon family. Weber and colleagues
present an animation showing the normal Ac element transposition process. http://jzhang.public.iastate.edu/transposition
Retrotransposons are also called transposons via RNA intermediates and are a
subclass of transposons. They are genetic elements that move around the genome
and leave copies of themselves behind. Retrotransposons are only active in
cancer cells and cells that turn into eggs and sperm, The authors noted that
retrotransposons, which do not move around the genome any more, may still
regulate the expression of nearby genes.
Tian Xu and colleagues 2005 found how to switch on and off the expression of
genes of the mouse genome to make it possible to study their functions. The
researchers mutate each gene, to observe the resulting changes, revealing thus
gene functions. Transposons, elements which can move from place to place in
the DNA are used in these studies. Transposons allow material to be inserted
Transposons revealing gene functions 
Transposons have proved to be valuable genetic tools for many organisms, but not
for vertebrates and mammals. Xu and colleagues used the transposon piggyBac from
the cabbage looper moth in mouse and human cell lines. A red fluorescent protein
and an enzyme changing the colour of a mouse from white to black was added to
work as a marker. Expressions of the altered genes were inherited though five
generations. The PiggyBac transposon can be removed from the next generation by
breeding with a mouse bearing an enzyme which excises the transposon. The team
of Xu is scaling up piggyBac for the Mouse Functional Genome Project.
The project tries to mutate the majority of mouse genes in China to understand
the functions of the mammalian genes in context and to identify the causes of
complex diseases having a genetic background in mammals The project aims to close
the gap between genotype and phenotype studying the function of isolated proteins
extended to their functional context in the cellular environment. 
Metabolomics is, according to a definition by Daviss, the "systematic study of
the unique chemical fingerprints that specific cellular processes leave behind".
It is the study of their small-molecule metabolite profiles
. The metabolome represents the collection of
all metabolites in a biological organism, which are the end products of its
gene expression, and can give an instantaneous snapshot of the physiology of
New terminology emerges with the new fields of science: omics refers fields in
biology which have such a suffix genomics or proteomics, and omes referes to
genome and proteome, which is the entire complement of proteins
expressed by a genome, cell, tissue or organism.
The laboratory will be maintained by the University of Birmigham, which believes
that this new area of science will improve understanding of how pollutants can
impact individuals and their health.
Righetti and colleagues 2010 looked at the protein composition of beer which
are important for the formation, texture, and stability of the of the beer
foam, including 20 barley proteins, 40 proteins from yeast genes, and two
proteins from corn. Saccharomyces cerevisiae, Saccharomyces bayanus and
Saccharomyces pastorianus used in the malting process for lager beer were
analysed and a widespread proteome of beer was established.
Proteome is the entire set of proteins expressed by a genome,
cell, tissue or organism.
The authors say that brewers may now use these findings to reduce off-flavour
proteins or to increase flavour and texture improving proteins during the
Dunn et al. 2012 describe a multi-species microarray platform and the array-Comparative Genomic Hybridization (aCGH) of the genomes of several Saccharomyces cerevisiae and S. paradoxus, S. mikatae, S. kudriavzevii, S. uvarum, S. kluyveri and S. castellii.
The technique is able to identify variations in copy number among different yeasts and determines the evolutionary relationships without sequencing the whole genome.
Applying this technique, the authors found interspecific hybridization events, introgression events, and pervasive copy number variation (CNV). The data suggest that yeasts, which normally reproduce asexually, had exchanged genes between strains of Sacchromyces cerevisiae and also between different species of yeast. These variations took place in free nature and during use by the industry.
The data presented by the authors may find the genomic regions responsible for the adaptation to different industrial milieus, and help to explain domestication of Sacharomyces cerevisiae.
Industrial environment made Saccharomyces cerevisiae to face numerous generations of artificial selection resulting in genetically different strains of industrial interest.
To highlight genome variations of industrial yeasts, Borneman et al. 2011 analysed the whole-genome assemblies of wine and brewing strains of Saccharomyces cerevisiae. The six yeasts which were studied presented clear signatures for each industrial class of yeast. The data of this study unveils more than twenty genes which had been unknown before. Furthermore, a cluster of five open reading frames (ORFs) of wine and bioethanol were identified at different genomic locations involving a circular DNA intermediate. ORFs are DNA sequences that does not contain a stop codon in a given reading frame. The authors stress that many ORFs and modes of genetic transmission of industrial yeasts are still unknown.
Abadio and colleagues 201, using comparative genomics, selected 10 genes present in pathogenic fungi which are absent in the human genome and may be used as anti-fungal drug target. The authors concentrated their researches on trr1 that encodes for thioredoxin reductase, rim8 that encodes for a protein involved in the proteolytic activation of a transcriptional factor in response to alkaline pH, kre2 that encodes for alpha-1,2-mannosyltransferase and erg6 that encodes for delta (24)-sterol C-methyltransferase. Drug side effects are not expected because these genes are not present in the human genome, stress the authors.
According to the Metabolomics Society, metabolomics is a newly emerging field of
"omics" research concerned with the comprehensive characterization
of the small molecule metabolites in biological systems. The Society believes that
metabolomics can assess the metabolic status and global biochemical events
associated with a cellular or biological system, and reveal both the
physiological state of a cell or organism and of their responses to environment.
UK, USA and Australia are the most active countries researching in metabolomics.
The European Nutrigenomics Organisation is a network linking
genomics, nutrition and health research.
A key objective of the network will be the development, data warehousing and
exploitation of nutrition and health-related bioinformatics for the benefit of
European nutrition researchers, and for the community as a whole.
Yilmaz and the Microbial Genomics and Bioinformatics Group, Max Planck Institute for Marine Microbiology, Bremen, Germany presented a standard developed by the Genomic Standards Consortium (GSC) minimum information for reporting marker gene sequences (MIMARKS), how to describe the environment (environmental packages) from which a biological sample originates, how to describe sequence data and provide a single access point of entry to GSC checklists. Furthermore minimum information about any (x) sequence (MixS) is presented.
An Epigenome consists of athe complete record of the chemical changes to the DNA and histone proteins of an organism, which can be passed down to an organism's offspring. Epigenetics is one of the current topics in cancer research drawing active research. Cancer cells are characterized by a large genomic hypomethylation, CpG island promoter hypermethylation of tumor suppressor genes, an altered histone code for critical genes and a global loss of monoacetylated and trimethylated histone H4.
Epigenetics is the study of heritable changes in gene expression or cellular phenotype caused by mechanisms other than changes in the underlying DNA sequence. It refers to functionally relevant modifications to the genome, such as DNA methylation and histone modification, that do not involve a change in the nucleotide sequence.
Bart De Moor et al. 2009 propose a kernel-based approach for clinical
decision support in which many genome-wide data sources are combined using an
As supervised classification algorithm, a weighted Least Squares Support Vector
The authors stress the importance of fusing more than one source of
genome-wide data such as the genome, transcriptome, proteome, and epigenome
linked by a methodological integration framework. The authors used this
framework on a rectal cancer data set containing microarray and proteomics
data and a prostate cancer data set containing microarray and genomics data.
They noted the improving of the prediction of all outcomes when more than one
genome-wide data set was considered.
The authors concluded that integrating multiple genome-wide data sources
increases the predictive performance of clinical decision support models in
patient tailored therapy applied to a rectal cancer data set containing microarray and proteomics data and a prostate cancer data set containing microarray and genomics data.
Teschendorff et al 2012 demonstrated that epigenetic changes in normal cells can predict the risk of cancer. The DNA methylation (DNAm) profile, in combination with human papilloma virus (HPV) infection, are a key factor in determining cervical cancer risk. 
The authors determined the DNA methylation (DNAm) profiles of over 27,000 CpGs in cytologically normal cells of the uterine cervix from 152 women. The samples had been collected years before the onset of any sign of cancer and were compared with data of women who remained disease-free. Data and samples of the ARTISTIC trial  and a statistical algorithm called EVORA (Epigenetic Variable Outliers for Risk prediction Analysis) were used in this study.
Many CpGs differed between women who developed a non-invasive cervical cancer within 3 years and those who remained disease-free. These CpGs presented methylation profiles similar age-associated DNA methylation changes in normal tissue. The authors stress that only 0.1% of CpGs in the human genome are known. Further studies may improve cancer prediction.
CpG sites are regions of DNA where a cytosine nucleotide is linked by one phosphate a guanine nucleotide in a linear sequence (cytosine- p - guanine). The study of methylation of the cytosine within a gene and its effects is a wide field of epigenetics. 
According to the UK Royal Society "Synthetic biology is an emerging area of research that can broadly be described as the design and construction of novel artificial biological pathways, organisms or devices, or the redesign of existing natural biological systems."
Synthetic biology aims to design and construct new biological functions and systems not found in nature.
Synthetic Biology 
Systems biology and synthetic biology use next-generation sequencing (NGS) and mass spectroscopy (MS) to understand the interactions of genes, proteins and small molecules. Roukos 2012 describe a new view of cellular signaling circuits, and redesigning and editing genetic code for a systems medicine-based applications in medicine, such as the personalized disease-risk assessment. This application is based on personal genomics using NGS, genome-wide association studies and epigenome-wide association studies (EWAS).
Systems biology and synthetic biology 
System biology looks at gene-gene, protein-protein interactions, and biomolecular networks, in contrast to a single gene or a molecule. Complex chronic diseases such as cancer, diabetes, cancer, and a variety of disorders, including immunological, cardiovascular, neurological and psychiatric diseases emerge from dysregulated genetic and biological systems interactions and cell signal transduction circuits. The next-generation medicine will base on such interactive network diagnostics combining these new field with high-throughput technologies.
Synthetic biology investigates the systematic construction of biological systems with cells being built module by module based on a bottom-up engineering strategy, instead of using top-down approaches usually used by systems biology.
The interconnection between system biology and synthetic biology is demonstrated by Noirel et al. 2009 inserting a light-receptor circuit coupled with lactose metabolism in a strain of Escherichia coli resulting in useful proteomic informations on the relationship between new circuits and chassis in synthetic biology applications. 
A report published by 111 organisations claim for more oversight and regulations by the government. The report stresses that risk assessment and cost-benefit analyses used to regulate synthetic biology are based on biotechnology regulations. These regulations are insufficient to cope with the new technology.
The report provides recommendations for managing new biological techniques for building and remaking organisms for research and commercial uses ranging from medicines to biofuels. Suggested regulations include a precautionary approach with an oversight mechanism suited for the unique characteristics of synthetic organisms and their products.
The group calls for a ban to manipulate the human genome or the genomes of microbes in and on the human body. The group also calls for a full disclosure of the nature of the synthetic organisms, tests, and asks for a moratorium on the release and commercial use of synthetic organisms until these regulations are implemented.
A presidential commission on bioethics in 2010 said that there are no need for new regulations for synthetic biology. The group, leaded by Friends of the World, increased their activities thereafter.
According to Ottman et al. 2012 meta-omics studies the intestinal microbiota. Met-omics comprises: Metagenomics which is DNA-based, metatranscriptomics which studies the total transcribed RNA, metaproteomics focuses on protein levels and metabolomics describes metabolic profiles.
The genetic background, age, diet, and health status of the host influence the composition and activity of the microbiota. The intestinal microbial metagenome is closely related to mechanisms for signalling, vitamin production and glycan, amino-acid and xenobiotic metabolism. The activity and composition of the microbiota is affected by genetic background, age, diet, and health status of the host, and differs in formula-fed babies, malnourished infants, elderly, obesity and inflammatory bowel diseases (IBD).  The obesity-induced gut microbiota imbalance, is characterized by increased Firmicutes to Bacteroidetes ratio (metagenomics) and of the so called "core microbiome", focusing on the gut microbiota at a gene-level. The link of the gut microbiota to nonalcoholic fatty liver disease in insulin-resistant mice was cleared in metabolomic studies. Serino et al 2012 suggest to extend studies to lipopolysaccharides, stressing that these Gram negative proinflammatory molecules are known to cause metabolic diseases. 
Antibiotics administered in low doses have been widely used as growth promoters in livestock sector altering the gut microbiome as well as its metabolic capabilities. Metabolism of carbohydrates, short-chain fatty acids, increases in colonic short-chain fatty acid levels, and alterations hepatic metabolism of lipids and cholesterol are affected. Cho et al. 2012 found that administering low levels of antibiotics to young mice altered their gut microbiome increasing adiposity and hormone levels linked to obesity. 
Trasande et al. 2012 report that exposure to antibiotics during the first 6 months of life is associated with consistent increases in body mass from 10 to 38 months. No association of antibiotics with obesity was found if the exposure takes place at the age of 6 to 23 month. In face of increasing childhood obesity the authors call for further studies on this issue. 
Farmers add antibiotics into pig, cattle and chicken feed to promote growth and fatten up the animals more quickly. According to Blaser 2009 antibiotics exert similar effect on children. 
Researchers compared the microflora of the western lifestyle with the microbiota of indigenous populations in the Amazon. The scientists took swab samples from stool, hands, feet, nose and mouth of a population of hunter-gatherers deep in the Amazon forest, trying to find the original bacterial flora of mankind and compared it with samples of indigenous population which already had contact with western life in the cities of Iquitos and Manaus.
First results of the study indicate that a Western lifestyle is harmful to bacterial communities. The use of antibiotics, rising number of cesarean section births, the reduction of family size and excessive hygiene are changing the microbiota of human kind causing some of modern diseases, says Dominguez-Bello, a member of the Amazon expedition. Disease is a result of an imbalance between the bacterial population and the human host. More than 25 different diseases and syndromes are known to be linked to an abnormal microflora.
The association of men and a gut microbiota, formed a superorganism which has been successful since prehistoric times. The scientists stress that this superorganism is under threats such as presented by the synthetic antibiotic ciprofloxacin which decimates the complete gut bacteria in only two treatment cycles. Bacteria recolonise the gut, however, fail to attain the original degree of diversity. A debilitating microbial imbalance known as dysbiosis may take place, says Martin Blaser. This leads to allergic disorders, chronic inflammation of the small intestine, intestinal cancer, type 2 diabetes, pathological obesity, Alzheimer's, Parkinson's, multiple sclerosis and autism.
During normal birth procedure, the child gets in contact with the lactobicilli of the mother. Such bacteria are needed to digest the maternal milk. An sterile cesarean section birth the baby is colonised by bacteria of the delivery room. While 16 per cent of babies born by C-section present obesity at the age of three, only 7,5 per cent of babies with normal delivery are overweighted. Based on experiments with animals, Blaser has discovered that an abnormal bacterial colonization can cause obesity. 
Probiotic drinks and yoghurts with lactic acid bacteria are marketed to improve the intestinal flora, however, studies say that bacteria ingested with the food are unable to to establish their microbiota in the gut.
It is therefore being suggested to transplant bacteria from the stool of a healthy individual to a patient. Faecal microbiota transplantation is performed administering saline solution via enema to a patient of chronic diarrhoea and may be used to treat obesity and diabetes, according to Willem de Vos et al. 2012. The study sees a way to use particularly beneficial bacterial strains to heal the microbiota altered by western lifestyle. Dominguez-Bello and Blaser hope to find the best gut microbiota among the native population of the Amazon region. 
Lemon et al. 2012 sees future probiotics as fecal transplant in a casule. New diagnostic tools will be needed to measure community function instead of looking at the composition of the microbiota. 
According to Zipursky et al. 2012 Fecal Microbiota Transplantation, is an effective alternative therapy for recurrent Clostridium difficile infection. Its unappealing nature causes that it is seldom used. Physicians believe that patients are not inclined to such treatment. The authors report, however, that despite aversions, most patients consider it as a treatment alternative for recurrent Clostridium difficile infection.
The South of the United States presented the highest antibiotic use (21.4% of medication). Patients in Western states received antibiotics the least, at about 17.4% of patients. The variation in antibiotics use was not linked to prevalence of infections, and regions with high use of antibiotics had often lower rates of pneumonia, says the study of Zhang et al. 2012. The authors call for programs to reduce unnecessary use of antibiotics, reducing the formation of antibiotics resistant bacteria and risks of adverse effects of the drug. 
Fairlie et al. 2012 report overuse of broad-spectrum antibiotics, such as quinolones and macrolides antibiotics in the treatment of acute sinusitis which are mostly of viral origin. Such medication is of little use, say the authors. 
Gut bacteria from the phylum Firmicutes increase the body's intake of calories from food. The microbiota increase epithelial lipid droplets (LD) number formation in the intestinal epithelium and liver in a diet dependent manner. Intake of food leads to an increase of Firmicutes bacteria in the intestine, increasing the number of small-sized epithelial LD number, whereas LD size was increased by other bacterial types. Semova et al.2012 conclude that different members of the intestinal microbiota promote fatty acids absorption via distinct mechanisms, and diet-induced alterations in microbiota composition might influence fat absorption and the regulation of host energy balance. Modification of intestinal bacteria may therefore improve absorption in case of undernutrition or reduced calorie uptake in obese individuals. 
Gordon et al. 2012 stress that childhood undernutrition is a global health problem that cannot be attributed to food insecurity alone. The authors point to the fact that the gut microbiota may be the cause of the health disorder. They call for an improved knowledge of the interrelationships between breast milk composition and the development of the microbiota and influence on the immune system. 
Obesity and high fat diet relate to a specific gut microbiota, which is enriched in Firmicutes and with less Bacterioidetes. Microbiota can also play a role in the development of hepatic steatosis, necroinflammation and fibrosis. Researchers found an associations between small intestinal bacterial overgrowth and nonalcoholic fatty liver disease caused by an activation of the Toll-like receptor-4 signaling cascade. Probiotics may be helpful in treatment of this disease. 
Bacteroidetes, are known to possess very large numbers of genes that encode carbohydrate active enzymes and can switch readily between different energy sources in the gut depending on availability, initiating the fermentation of complex non-digestible dietary carbohydrates and host-derived glycans. More nutritionally specialized bacteria such as Firmicutes, Actinobacteria and Verrucomicrobium phyla degrade complex substrates such as plant cell wall glycans, starch particles and mucin, report Flint et al. 2012. 
The Bacteroidetes use a series of membrane protein complexes, termed Sus-like systems, for catabolism of many complex carbohydrates of plant cell wall glycans. The human gut Bacteroides thetaiotaomicron and Bacteroides ovatus, are capable of utilizing nearly all of the major plant and host glycans, including rhamnogalacturonan II highly resistant to microbial degradation.
The Sus-like systems and polysaccharide utilization loci (PULs) phenotypes of gut bacteria 
Martens et al 2011 identified the polysaccharide utilization loci (PULs) that encode individual Sus-like systems that target various plant polysaccharides. The authors report that B. ovatus possesses PULs phenotype capable to degradation hemicellulosic polysaccharides. This phenotype is absent from B. thetaiotaomicron, which, on his turn, can metabolize the human mucin O-glycan this ability is absent from B. ovatus. Each PUL is highly specific for a defined cell wall polymer, indicating a high specialisation of gut bacteria differing them from bacteria of other habitats. Dietary intake of nondigestible carbohydrates influences microbial fermentation and total bacterial numbers in the colon. Flint 2012 summarizes evidences from molecular ecology which say that the amount and type of nondigestible carbohydrates, such as resistant starch, non-starch polysaccharides, and prebiotics influences the species composition of the intestinal microbiota. The microbiota responds to short-term dietary interventions, but also to long-term dietary intake.
Fusobacterium nucleatum is a member of the oral biofilm associated with caries, gingivitis, and periodontitis. It was also found in cases of acute apendicitis  and ulcerative colitis, the later is a risk factor for colon cancer. The prevalence of Fusobacterium is uncommon in the normal gut microbiome. Two studies propose the hypothesis that Fusobacterium nucleatum is an agent of colorectal cancer.
Holt et al 2011, using metagenomics methods techniques, sequenced the whole DNA present in colon cancer tissue and compared this to RNA from normal colon tissue, looking for sequences that originate from microorganisms.The authors found Fusobacterium sequences was the leading bacteria of the microbiota in colorectal tumor. The bacterium was also found to have a positive association with lymph node metastasis.
Kostic et al 2011 also found Fusobacterium as leading sequences in carcinomas using quantitative PCR and 16S rDNA sequence analysis. The bacteria was visualized within colorectal tumors using FISH.
Both studies stress that it remains unclear whether Fusobacterium nucleatum infection is a cause or consequence of colorectal tumors. Antibiotics or vaccines may be useful to treat or prevent colonrectal cancer, if further proves Fusobacterium nucleatum as disease agent are found.
Tovey et al. 2011 describe a case of Fusobacterium nucleatum causing a pyogenic liver abscess together with rectal cancer. The authors suggest that the presence of Fusobacterium nucleatum may be a symptoms of colonic cancer, similar to Streptococcus bovis in cancer bacteraemia which is accepted as a diagnostic marker for occult colonic malignancy.  
Transcriptome is the sum of all RNA molecules present in one or a population of cells. Transcriptome analysis can provide informations on the interactions of oral polymicrobial interactions and biofilm, Redanz et al 2011 developed a transcriptome array covering the full genomes of 5 important members of the oral microbiot (Streptococcus sanguinis, Streptococcus mutans, Fusobacterium nucleatum, Aggregatibacter actinomycetemcomitans, and Porphyromonas gingivalis). The authors stress that the described array allows transcriptome studies on multi-species oral biofilm interactions and may be useful to study oral biofilm.
Moore 2011describes massively parallel sequencing technology which samples the transcriptome of given tissues. Transcripts at only a few copies per cell are readily detectable in human tissue samples. It is a highly sensitive method for detecting infectious agents associated with human tissue pathology. 
Kevin Chen and Lior Pachter (researchers at the University of California, Berkeley) defined metagenomics as "the application of modern genomics techniques to the study of communities of microbial organisms directly in their natural environments, bypassing the need for isolation and lab cultivation of individual species."
Metagenomics methods sequences bulk DNA or RNA from disease tissue. Computer programs subtract all human sequences. The non-tissue related data are compared with known microbial sequences and identifies infectious agents. Feng et al. 2008 used metagenomics to discover a novel polyomavirus in Merkel Cell carcinoma. 
According to Chen and Pachter 2005 metagenomics is the application of modern genomics techniques to the study of communities of microbial organisms directly in their natural environments, bypassing the need for isolation and lab cultivation of individual species. 
Fluorescence in situ hybridization (FISH) is a technique used to identify the presence of specific chromosomes or chromosomal regions through hybridization (attachment) of fluorescently-labeled DNA probes to denatured chromosomal DNA.
Fluorescence in situ hybridization (FISH) 
FISH uses fluorescent particles that bind to only those parts of the chromosome with which they show a high degree of sequence complementarity. Fluorescence microscopy is used for the visualization. The technique is often used for finding specific features in DNA for use in medicine, and species identification. It can detect directly the presence of a suspected bacteria or virus on small samples of tissue, it can also be used to compare the genomes of two biological species. It is often used in microbial ecology, to identify microorganisms and analyse biofilms. Müller et al 2007 presented a complex FISH technique with 6 different Fluorochromes.
The aim of the community ist to provide computing power to studies in scientific field such as:
- New and existing infectious disease research - development of treatments for HIV/AIDS, Malaria, Severe Acute Respiratory Syndrome (SARS), etc.
- and disease - functions of proteins that are coded by human genes and how they might relate to cures for common diseases.
- Environmental research - meteorology and severe weather warning, pollution, remediation, climate modelling, and others.
- Natural disasters and hunger - earthquake warning, information on improving crop yields and livestock production, and evaluation of the supply of critical natural resources such as water.
Ongoing studies are:
The mission of Discovering Dengue Drugs - Together - is to identify promising drug candidates to combat the Dengue, Hepatitis C, West Nile, Yellow Fever, and other related viruses. These drugs target the viral NS3 protease, an enzyme critical for virus replication, and its amino acid sequence and atomic structure are very similar among the different disease-causing flaviviruses. In this study advanced structure-based computational drug discovery methods are used to identify small molecule protease inhibitors.
The Bonneau Lab is working on microbiome projects such as analysing the malaria parasite Plasmodium Yoelii Yoelii. The team stresses that this rodent malaria parasite is important for understanding the function of human malaria. 
A microbiome is the totality of microbes, their genetic elements (genomes), and environmental interactions in a defined environment. The microbiome usually includes microbiota and their complete genetic elements. Researchers in the Human Microbiome Project are sampling and analyzing the genome of microbes from five sites on the human body: nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract. Microbiome studies the microorganisms included as part of the human genome, because of their influence on human physiology.
The Human Microbiome Project (HMP) is a United States National Institutes of Health initiative with the goal of identifying and characterizing the microorganisms which are found in association with both healthy and diseased humans (their microbial flora). This microbiome project is to test if changes in the human microbiome are associated with human health or disease. 
Defining the human being as an individual developed out of a fertilised egg containing genes from father and mother is insufficient to describe an individual. Microbiologists increase the scope of the definition by including the notion of an ecosystem which also embraces bacteria, fungi and archaea. This aggregate of microorganisms resides on the surface and in deep layers of skin, in the saliva and oral mucosa, in the conjunctiva, and in the gastrointestinal tracts and is known as human microbiome. This system provides advantage for both, host and colonising microorganisms. However changes in the the microbiome may result in diseases such as obesity, diabetes, heart diseases, asthma, multiple sclerosis and neurological conditions such as autism. 
The Common Fund's Human Microbiome Project (HMP) aims to characterize the microbial communities living in community with the human body, and determines the role of these microbes in human health and disease.
Metagenomics is the study of a collection of genetic material (genomes) from a mixed community of organisms. Many bacteria, fungi and viruses cannot be cultured in standard tecniques. However, new genomic techniques can identify minute amounts of microbial DNA in an individual and determine its identity by comparing the genetic signature to known sequences in the HMP reference collection database.
According to Collins of the Human Microbiome Project, the new data will profoundly modify diagnose, treatment and prevention of many diseases.
The first phase of this initiative includes the sequencing of hundreds of microbial reference genomes, coupled to metagenomic sequencing from multiple body sites. The institute launched 178 microbial genomes in the reference collection of a total of approximately 900 microbial genomes of bacteria, viruses and fungi. Microorganisms that reside in or on the human body outnumber cells in the human body by 10 to 1, some of them are pathogens, others are needed for a healthy life. These studies already identified unknown proteins produced by bacteria that live in the stomach that may cause gastric ulceration, other proteins are associated sugars and amino acids are metabolized. Another 29,693 previously undiscovered, unique proteins were included in the reference collection. The reference collection has nearly twice the amount of microbial diversity than is represented by microbial genomes already in public databases.
Comparing 16.8 million microbial sequences found in public databases to the genome sequences in the HMP reference collection the researchers found 62 genomes in the reference collection to be similar to 11.3 million microbial sequences in public databases and 6.9 million correspond with genome sequences in the reference collection. However, more research must be done because at least one-third of the metagenomic sequences are still not represented by any genome in the reference collection and that this analysis focused only on the gastrointestinal tract.
The Human Microbiome Project report that the microbiome of healthy individuals differ substancially, whereas diet, environment, host genetics and early microbial exposure seems to be implicated. Strong niche specialization both within and among individuals. The study provides data which delineate the configurations of healthy gut microbial communities for future studies of the epidemiology, ecology and translational applications of the human microbiome. 
According to Nicholson et al. 2012, the gut microbiota interacts with metbolic pathways host-microbiota metabolic, signaling, and immune-inflammatory axes that physiologically connect the gut, liver, muscle, and brain.
The human microbiomes is dominated by four phyla: The actinobacteria , Bacteroidetes, Firmicutes and Proteobacteria. Surprisingly, the microbiota may differ from one region to another. Yatsunenko et al. 2012 point out that children in Malawi and Venezuela have a normal bacterial population which differs from that of North Americans. Malawian microbiota has more riboflavin-producing bacteria and produces more glycoside hydrolase, and enzyme which turns glycans of mother's milk into suitable sugars as that of gut bacteria of North American children. 
Oligosaccharides of human milk promotes the growth of healthy bacteria such as Bifido microbiota and arrests the growth of infectious bacteria.
Gordon et al. 2006 reported that obesity is associated with changes in the abundance of two dominant bacterial divisions, Firmicutes and Bacteroidetes. Obese people have more Firmicutes and fewer Bacterioidetes than thin persons. The obese microbiome was found to have an increased yield of energy from the diet. Germ-free mice colonization with the "obese microbiota" results in obesity, while similar mice treated with a "lean microbiota" present less body fat.
Microbiome and Obesity 
"Obese microbiota" may also produce an hormone that facilitates fat storage, together with an enzyme that stops fat burning. This may explain why antibiotics added to cattle feed improves weight gain adding muscle mass and fat. Malnutrition is an important cause of obesity, however, readjusting the composition of gut bacteria may help to treat certain types of overweight. 
There is also being discussed that the microbiome may influence body weight inducing a low-grade inflammation with lipopolysaccharide, regulation of host genes responsible for energy expenditure and storage, and hormonal communication between the intestinal microbiome and the host. 
The 16S rRNA gene pyrosequenced gut microbiota of the Coriobacteriaceae family stimulate glycogenesis and triglyceride synthesis in the liver in association with modifications of hepatic Cyp8b1 expression and alteration of bile acid metabolites, including taurocholate and tauromuricholate, engaged in fat absorption. Expression and activity of major drug-metabolizing enzymes (Cyp3a11 and Cyp2c29) were also significantly stimulated. Claus et al.2011 concluded that the gut microbiota improves nutrients and drugs processing and improves pathways in a variety of organ systems.
Sczesnak et al 2011, in a study funded in part by the Human Microbiome Project, found that segmented filamentous bacteria (SFB) in mice and other mammals are known to affect the host immune system. The bacteria found in droppings from mice presented a genome that is much smaller than closely related species The SFB bacteria lack many genes related to metabolism which was probably lost while living as commensal because the bacteria rely on the host for a great deal of what they need to grow and survive. In fact these bacteria depend on their host. They try therefore to defend their host attracting proinflammatory TH17 cells in case of an invasion of pathogen bacteria.
The authors present the genome sequence of SFB which is a unique member of Clostridiales with a highly reduced genome. It is functionally related to members of the genus Clostridium and several pathogenic or commensal "minimal" genera, including Finegoldia, Mycoplasma, Borrelia, and Phytoplasma. As a gut commensal it is closely tied to host metabolism and immunity.
Segmented filamentous bacteria (SFB) can promote IL-17-dependent immune and autoimmune responses, gut-associated as well as systemic, including inflammatory arthritis and experimental autoimmune encephalomyelitis. SFB colonisation protected females, but not males, from diabetes, according to Kriegel et al. 2011.  Khoruts and Sadowsky 2011 report an example of the importance of gut microbiota and interaction with its host. The authors report treatment of Clostridium difficile gut infections with foecal transferes after collapse of the microbial community caused by antibiotic therapy or infection with pathogen. A better understanding of the interactions of humans with bacteria and synergistic are expected to result of these studies. 
According to Laparra and Sanz 2010 the beneficial effects of prebiotics mainly relay on their influence on the gut microbiota composition and their ability to generate fermentation products which may improve the status of immunity and metabolism of the host. The gut microbiota enhance the antioxidant effects of polyphenols transforming them in bioavailable compounds. Prebiotics may stimulate beneficial bacteria inhibiting pathogenic strains. The modulation of the intestinal microbiota can be used to treat intertinal disfunctions and may enhance the biological activity of micronutrients.based on the interactions of gut bacteria on human health. 
Roberfroidet al 2010 define as 'normobiosis' the composition of the gut 'ecosystem' in which micro-organisms with potential health benefits predominate in number over potentially harmful ones, in contrast to 'dysbiosis', in which one or a few potentially harmful micro-organisms are dominant, thus creating a disease-prone situation. The authors concluded that prebiotics may cause a selective modification in the composition of the gut microbiota leading to normobiosis could either induce beneficial physiological effects or reducing the risk of dysbiosis and associated intestinal and systemic pathologies. 
The composition of soil microbiological population is complex. Metagenomics, the study of the entire genome of soil biota, provide a tool to discover new species, genes or novel molecules that are relevant for biotechnology and agricultural applications.
Soil metagenome 
Assessing the microbiological population of soil and sediments encounters difficulties as most of the microorganisms in nature are uncultivable. Soil metagenome are suggested to study the genetic resources from terrestrial environments. Rajendhran and Gunasekaran 2008 stress that methods are being developed for a direct isolation of environmental DNAs which are cloneable and can be used in genomic DNA libraries with subsequent high-throughput sequencing or library screening.  van Elsas et al. 2008 describe molecular tools to assess the collective soil metagenome as an alternative to cultivation. The authors aim to explore genes of biotechnological interest, such as the metagenome of disease-suppressive soils with antibiotic biosynthetic clusters. The author highlights the help of the disease-suppressive soils project METACONTROL to handle the high amount of data of soil metagenome.
Reigstad at al 2011 point out that metagenomics the metabolisms from rather uninvestigated organisms such as the ammonia-oxidizing archaea. For that methods were used to isolate high-molecular weight (hmw) DNA from soil and hot spring samples and mud, produce large-insert metagenomic libraries, analyse the resulting genomic fragments, and screen the libraries for genes of interest. 
Crop plants are more resistant to diseases growing on certain soils compared to other soils. This may be linked to exceptional ecosystems where the community of microbes inhibits root pathogens, such as certain moulds.
Mendes and colleagues 2011 identified more than 33,000 bacterial and archaeal species and genes which are linked to inhibition of pathogens using PhyloChip-based metagenomics, together with culture-dependent functional analyses. The authors report that Proteobacteria, Firmicutes, and Actinobacteria, and nonribosomal peptide synthetases of gama-Proteobacteria were linked to disease suppressionwere shown to have disease-suppressive activity governed by.  Lee and Hallam present a protocol for extracting high molecular weight, microbial community genomic DNA from soils and sediments suitable for constructing large insert environmental genomic libraries..This protocol uses mechanical grinding and beta-mercaptoethanol for cell lysis.
Chloroform-isoamyl alcohol and isopropyl alcohol is used to isolate the genomic DNA, together with guanidine isothiocyanate and hexadecyltrimethylammonium bromide as buffer. To reduce impurities such as proteins and humic acids, the isolated genomic DNA can be further purified using cesium chloride (CsCl). The whole process takes two and a half days, therefore shearing, severe vortexing and harsh pipetting should be avoided in order to prevent damage of the DNA.
According to a study of Orešič et al 2011, blood serum analysis may predict future development of Alzheimer's Disease (AD) before symptoms of the disease occur. The analysis identifies molecular changes associated with Alzheimer Disease years in advance. These biomarkers suggest a state of increased hypoxia.
Blood serum metagenomic analysis may predict future development of Alzheimer's Disease years ahead of the first symptoms 
The authors explain that mild cognitive impairment (MCI) is a transition phase between normal aging and Alzheimer's disease. MCI increases the risk of Alzheimer's disease, but has several possible outcomes, including even improvement back to normal cognition.
The metabolomic research on changes in lipids related to the disease detect small metabolites blood profile used as a good predictive markers.
The authors stress that AD patients were characterized by diminished ether phospholipids, phosphatidylcholines, sphingomyelins, and sterols.
The molecular signature of the MCI patients progressing to AD is leaded by 2,4-dihydroxybutanoic acid as an indicated the potential involvement of hypoxia. The pentose phosphate pathway also causes hypoxia and oxidative stress plays a role in early stage of AD.
Dr. Orešič and colleagues point out that reduction of several membrane phospholipids in patients serum, contrary to foregoing studies, could not be seen as early predictors of Alzheimer's Disease, but may be a later event. The authors suggest, therefore, to see hypoxia as early predictor of AD instead of lipid-changes.
Other approaches to a early diagnosis of AD were such as the study of Li et al. 2010 aiming to was map potential biomarkers in plasma. using ultra performance liquid chromatography/mass spectrometry (UPLC/MS) and metabonomics approach. The principal component analysis (PCA) of UPLC/MS spectra showed that metabolic changes between two groups. The authors report nine potential biomarkers in correlation with the extent of AD, such as lysophosphatidylcholines LPCs, sphingosine and tryptophan may be potential early markers of the disease.
Antibiotic resistance in soil bacteria had its beginning much before the start of medical use of antibiotics. There are evidences that soil bacteria developed antibiotics resistance genes responding to pressure from fungi and other bacteria. The primary antibiotic resistance gene pool originated and diversified within the environmental bacterial communities The soil bacteria exchanged such genes with pathogen bacteria. Until recently, no lateral gene transfer from antibiotic-producing bacteria was active in forming the pool of antibiotic resistance genes in clinically relevant and commensal bacteria, says Aminov and Mackie 2007. 
Forsberg et al. 2012 describe the antibiotica resistance of soil bacteria which have resistance cassettes against five classes of antibiotics, such as β -lactams, aminoglycosides, amphenicols, sulfonamides, and tetracyclines. The bacteria present genes which are similar to human pathogens. These genes are noncoding regions as well as multiple mobilization sequences which demonstrates recent lateral exchange. These genetic constructions are ways by which soil bacteria and pathogens exchange to antibiotic resistance genes. 
Cantón 2009 stresses that metagenomic tools and phylogenetic analysis lead to the collection of all the antibiotic resistance genes and their precursors in both pathogenic and non-pathogenic bacteria. The complex pool of antibiotic resistance genes and genetic elements participating in resistance gene transfer is called "resistome".
The resistome unites antibiotic resistance genes and gene elements
Examples of exchange of such resistance genes in multidrug-resistant bacteria are ribosomal methylases affecting aminoglycosides (armA, rtmB), methyltransferases affecting linezolid (cfr) or plasmid-mediated efflux pumps conferring low-level fluoroquinolone resistance (qepA). These genes are also found in antibiotic-producing bacteria. Resistance genes, such as the qnr and the bla(CTX) genes compromising the activity of fluoroquinolones and extended-spectrum cephalosporins, respectively are present in ancient soil bacteria which are not antibiotic producers. Cantón points to the importance of the concept of resistome to unite the whole reservoir of antibiotic genes and gene elements. 
Gerard D. Wright proposed the concept of "resistome" for the collection of all the antibiotic resistance genes and their precursors in both pathogenic and non-pathogenic bacteria. 
This complete set of antibiotic resistance genes is composed of four different types of genes:
1- Resistance genes found on pathogenic bacteria.
2- Resistance genes found on antibiotic producers: The microorganisms such as soil-dwelling bacteria and fungi that naturally produce antibiotics developed protection against the antibiotics they produce. Recent exchange with human pathogenic bacteria are of concern.
3- Cryptic resistance genes: These genes are embedded in the bacterial chromosome but do not obviously confer resistance, because their level of expression is usually low or they are not expressed.
4- Precursor genes: These genes do not confer antibiotic resistance. However they encode proteins that confer to some kind of basal level activity against the antibiotic molecule or have affinity to the molecule. In both cases this interaction may evolve to a full resistance gene given the appropriate selection pressure. 
Rapidly growing mycobacteria (RGM) live in soil and water. Some strains are associated with abscesses or cellulitis following trauma in humans. Tetracyclines of human and farm animal therapies result in antibiotic residues which end up in the soil as manure exposing both clinical and soil RGM to pressure for resistance to tetracycline antibiotics.
Efflux pumps are more important for antibiotic resistance than horizontally transferred genes 
Kyselková et al. 2012 found no difference between the clinical and soil isolates in tetracycline resistance, suggesting low horizontal gene transfer, however, tet(V) and tap, which encode mycobacterial efflux pumps were found in both groups. Notably, these genes emerge now in species where they were unknown before. The authors concluded that intrinsic efflux pumps may be more important for tetracycline resistance than horizontally transferred genes in both soil and clinical rapidly growing mycobacteria, however their function must be further cleared.
Rinie van Est, Hanssen, Lucien: Genomics in the agrofood sector, An overview of social questions and dilemma; Rathenau Institute The Hague, The Netherlands, Deining Consultancy for Social Communication.
Foodnavigator: Nutrigenomics will underlie food future. 23.08.2007.
Mei Wang, Robert-Jan A. N. Lamers, Henrie A. A.J. Korthout, Joop H.J. van Nesselrooij, Renger F. Witkamp, Rob van der Heijden, Peter J. Voshol, Louis M. Havekes, Rob Verpoorte, Jan van der Greef: Metabolomics in the context of systems biology: bridging traditional Chinese medicine and molecular pharmacology. Volume 19 Issue 3, Pages 173 - 182 2005.
Cramer GR, Urano K, Delrot S, Pezzotti M, and Shinozaki K.
Effects of abiotic stress on plants: a systems biology perspective.
BMC Plant Biol, 11:163, 11 2011.
Bu Z and Callaway DJ.
Proteins move! protein dynamics and long-range allostery in cell signaling.
Adv Protein Chem Struct Biol, 83:163-221, 2011.
Mochida K and Shinozaki K.
Advances in omics and bioinformatics tools for systems analyses of plant functions. plant cell physiol.
52(12):2017-38, 12 2011.
Systems biology: New institute and applications.
Yale J Biol Med, 84(1):59-61, 3 2011.
National Institutes of Health NIH): Metabolomics Technology Development; September 29,2003.
Spranger, Joachim; Wegewitz, Uta; Bobbert, Thomas; Göhring, Isabel: Metabolomics in human blood; German Institute of Nutrition DIFE), Department Clinical Nutrition.
Plagemann, A; Rckert, J. C.; Friedrichs, J.; Götz, F.; Dörner, G.: Fetal and neonatal hyperinsulinism as risk factor of a lifelong enhanced diabetes susceptibility. In: Z. Laron; M. Karp eds) Genetic and Environmental Risc Factors for Typ I Diabetes IDDM). Freund Publishing House, Tel Aviv-London 1992) 73.
Berni Canani R, Di Costanzo M, Leone L, Bedogni G, Brambilla P, Cianfarani S, Nobili V, Pietrobelli A, and Agostoni C.
Epigenetic mechanisms elicited by nutrition in early life.
Nutr Res Rev, 18:1-8, 2011.
Berni Canani R, Di Costanzo M, and Leone L.
The epigenetic effects of butyrate: potential therapeutic implications for clinical practice.
Clinical Epigenetics, 4, 4 2012.
Slaughter A, Daniel X, Flors V, Luna E, Hohn B, and Mauch-Mani B.
Descendants of primed arabidopsis plants exhibit resistance to biotic stress.
Plant Physiol, 158(2):835-43, 2 2012.
Dowen RH, Pelizzola M, Schmitz RJ, Lister R, Dowen JM, Nery JR, Dixon JE, and Ecker JR.
From the cover: Pnas plus: Widespread dynamic dna methylation in response to biotic stress.
Proceedings of the National Academy of Sciences, 109(32):E2183, 2012.
Prime time for transgenerational defense.
Plant Physiol, 158(2):545, 2012.
Luna E, Bruce TJ, Roberts MR, and Ton J Flors V.
Next-generation systemic acquired resistance.
Plant Physiol, 158(2):844-53, 2 2012.
Rasmann S, De Vos M, Casteel CL, Tian D, Halitschke R, SunJY, Agrawal AA, Felton GW, and Jander G.
Herbivory in the previous generation primes plants for enhanced insect resistance.
Plant Physiol, 158(2):854-863, 2 2012.
Tools and landscapes of epigenetics.
Nature Immunology, pages 565-568, 11 2010.
Suzuki et al. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nature Genetics, 2009; DOI: 10.1038/ng.375.
Taft et al. Tiny RNAs associated with transcription start sites in animals. Nature Genetics, 2009; DOI: 10.1038/ng.312.
Weber, David; Pulletikurti, Vinay; Yu, Chuanhe; Zhang; Jianbo, Peterson, Thomas: Alternative Ac/Ds Transposition and Chromosomal Rearrangements in Maize. Illinois State University.
Faulkner et al. The regulated retrotransposon transcriptome of mammalian cells. Nature Genetics, 2009; DOI: 10.1038/ng.368.
Ding, Sheng; Li, Xiaohui Wu, Gang; Han, Min; Zhuang, Yuan; Xu, Tian : Efficient Transposition of the piggyBac (PB) Transposon in Mammalian Cells and Mice. Cell, Volume 122, Issue 3, 473-483, 12 August 2005 doi:10.1016/j.cell.2005.07.013.
B. Daviss, Growing pains for metabolomics, The Scientist, 19:25-28, April 25, 2005.
UK Investment and Trade Services: Birmingham gains first metabolomics lab. A facility supporting an emerging science will be set up at a UK university.
Fasoli E, Aldini G, Regazzoni L, Kravchuk AV, Citterio A, Righetti PG: Les Maîtres de l'Orge: The Proteome Content of Your Beer Mug. Journal of Proteome Research, 2010; 100909154150098 Doi: 10.1021/pr100551n.
Dunn B, Richter C, Kvitek DJ, Pugh T, and Sherlock G.
Analysis of the saccharomyces cerevisiae pan-genome reveals a pool of copy number variants distributed in diverse yeast strains from differing industrial environments.
Genome Res, 2 2012.
Borneman AR, Desany BA, Riches D, Affourtit JP, Forgan AH, Pretorius IS, Egholm M, and Chambers PJ.
Whole-genome comparison reveals novel genetic elements that characterize the genome of industrial strains of saccharomyces cerevisiae.
PLoS Genet, 7(2):e1001287, 2 2011.
Abadio AK, Kioshima ES, Teixeira MM, Martins NF, Maigret B, and Felipe MS.
Comparative genomics allowed the identification of drug targets against human fungal pathogens.
BMC Genomics, 12:75, 1 2011.
The European Nutrigenomics Organisation NuGO.
Yilmaz P et al.
Minimum information about a marker gene sequence (mimarks) and minimum information about any (x) sequence (mixs) specifications. microbial genomics and bioinformatics group, max planck institute for marine microbiology, bremen, germany.
Nat Biotechnol, 29(5):415-20, 5 2011.
Daemen, Anneleen; Gevaert, Olivier; Ojeda, Fabian; Debucquoy, Annelies; Suykens, Johan AK; Sempoux, Christine;Machiels, Jean-Pascal; Haustermans, Karin; De Moor,Bart : A kernel-based integration of genome-wide data for clinical decision support. Genome Medicine 2009, Published: 3 April 2009. 1:39doi:10.1186/gm39.
Teschendorff AE, Jones A, Fiegl H, Sargent A, Zhuang JJ, Kitchener HC, and Widschwendter M.
Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation.
Genome Med, 3 2012.
Cpg sites. wikipedia.
Synthetic biology. defining the concept.
Biotechnological, genomics and systems-synthetic biology revolution: redesigning genetic code for a pragmatic systems medicine.
Expert Rev Med Devices, 9(2):97-101, 3 2012.
Noirel J, Ow SY, Sanguinetti G, and Wright PC.
Systems biology meets synthetic biology: a case study of the metabolic effects of synthetic rewiring.
5(10):1214-23, 10 2009.
111 organizations call for synthetic biology moratorium. scienceinsider 13 mar 2012.
The principles for the oversight of synthetic biology.
Ottman N, Smidt H, de Vos WM, and Belzer C.
The function of our microbiota: who is out there and what do they do?
Front Cell Infect Microbiol, 2:104, 2012.
Serino M, Chabo C, and Burcelin R.
Intestinal microbiomics to define health and disease in human and mice.
Curr Pharm Biotechnol, 13(5):746-58, 4 2012.
Cho I, Yamanishi S, Cox L, Methé BA, Zavadil J, Li K, Gao Z, Mahana D, Raju K, Teitler I, Li H, Alekseyenko AV, and Blaser MJ.
Antibiotics in early life alter the murine colonic microbiome and adiposity.
Nature, 488(7413):621-6, 8 2012.
Trasande L, Blustein J, Liu M, Corwin E, Cox LM, and Blaser MJ.
Infant antibiotic exposures and early-life body mass.
Int J Obes (Lond), 8 2012.
Blaser MJ and Falkow S.
What are the consequences of the disappearing human microbiota?
Nat Rev Microbiol, 7(12):887-94, 12 2009.
Crucial colonizers western lifestyle disturbing key bacterial balance.
Lemon KP, Armitage GC, Relman DA, and Fischbach MA.
Microbiota-targeted therapies: an ecological perspective.
Sci Transl Med, 4(137):137rv5, 6 2012.
Zipursky JS, Sidorsky TI, Freedman CA, Sidorsky MN, and Kirkland KB.
Patient attitudes towards the use of fecal microbiota transplantation in the treatment of recurrent clostridium difficile infection.
Clin Infect Dis.
Zhang Y, Steinman MA, and Kaplan CM.
Geographic variation in outpatient antibiotic prescribing among older adults.
Arch Intern Med, pages 1-7, 2012.
Fairlie T, Shapiro DJ, Hersh AL, and Hicks LA.
National trends in visit rates and antibiotic prescribing for adults with acute sinusitis.
Arch Intern Med, pages 1-2, 2012.
Semova I, Carten JD, Stombaugh J, Mackey LC, Knight R, Farber SA, and Rawls JF.
Microbiota regulate intestinal absorption and metabolism of fatty acids in the zebrafish.
Cell Host Microbe, 12(3):277-88, 9 2012.
Gordon JI, Dewey KG, Mills DA, and Medzhitoy RM.
Malnutrition. the human gut microbiota and undernutrition.
Sci Transl Med, 4(137):ps12, 6 2012.
Machado MV and Cortez-Pinto H.
Gut microbiota and nonalcoholic fatty liver disease.
Ann Hepatol, 11(4):440-9, Jul-Aug 2012.
Flint hj and scott kp and duncan sh and louis p, forano e: Microbial degradation of complex carbohydrates in the gut.
Gut Microbes, 3(4):289-306, 7 2012.
Martens EC, Lowe EC, Chiang H, Pudlo NA, Wu M, McNulty NP, Abbott DW, Henrissat B, Gilbert HJ, Bolam DN, and Gordon JI.
Recognition and degradation of plant cell wall polysaccharides by two human gut symbionts.
PLoS Biol, 9(12):e1001221, 12 2011.
The impact of nutrition on the human microbiome.
Nutr Rev, 70(Supl 1):S10-3, 8 2012.
Castellarin M, Warren RL, Freeman D, Dreolini L, Krzywinski M, Strauss J, Barnes R, Watson P, Allen-Vercoe E, Moore RA, and Holt RA.
Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma.
Genome Research, 2011.
Swidsinski A, Dörffel Y, Loening-Baucke V, Tertychnyy A, Biche-Ool S, Stonogin S, Guo Y, and Sun ND.
Mucosal invasion by fusobacteria is a common feature of acute appendicitis in germany, russia, and china.
Saudi J Gastroenterol, 18(1):55-8, 1 2012.
Kostic AD, Gevers D, Pedamallu CS, Michaud M, Duke F, Earl AM, Ojesina AI, Jung J, Bass AJ, Tabernero J, Baselga J, Liu C, Shivdasani RA, Ogino S, Birren BW, Huttenhower C, Garrett WS, and Meyerson M.
Genomic analysis identifies association of fusobacterium with colorectal carcinoma.
Genome Research, 2011.
Tovey M, Rizvi FA, Raman S, and Wheatley KE.
Rectal cancer presenting as fusobacterium nucleatum pyogenic liver abscess: A case report.
International Journal of Case Reports and Images, 2(6):16-19, 2011.
Redanz S, Standar K, Podbielski A, and Kreikemeyer B.
A five-species transcriptome array for oral mixed-biofilm studies.
PLoS One, 6(12):e27827, 2011.
Moore RA, Warren RL, Freeman JD, Gustavsen JA, Chénard C, Friedman JM, Suttle CA, Zhao Y, and Holt RA.
The sensitivity of massively parallel sequencing for detecting candidate infectious agents associated with human tissue.
PLoS One, 6(5):e19838, 2011.
Feng H, Shuda M, Chang Y, and Moore PS.
Clonal integration of a polyomavirus in human merkel cell carcinoma.
Science, 319(5866):1096-100, 2 2008.
Chen K and Pachte L.
Bioinformatics for whole-genome shotgun sequencing of microbial communities.
PLoS Comput Biol, 1(2):e24.
Müller S, Neusser M, Köhler D, and Cremer M.
Preparation of complex dna probe sets for 3d fish with up to six different fluorochromes.
CSH Protoc, 5 2007.
World community grid.
Discovering dengue drugs - together-.
Hpf2 update - january 2011.
Human Microbiome Project (HMP) The National Institutes of Health NIH.
Human Microbiome Jumpstart Reference Strains Consortium.
A catalog of reference genomes from the human microbiome.
Science, 328(5981):994-9, 5 2010.
The nih common fund: Human microbiome project.
Human microbiome project consortium: Structure, function and diversity of the healthy human microbiome.
Nature, 486(7402):207-14, 6 2012.
Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, and Pettersson S.
Host-gut microbiota metabolic interactions.
Science, 336(6086):1262-7, 6 2012.
Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, Magris M, Hidalgo G, Baldassano RN, Anokhin AP, Heath AC, Warner B, Reeder J, Kuczynski J, Caporaso JG, Lozupone CA, Lauber C, Clemente JC, Knights D, Knight R, and Gordon JI.
Human gut microbiome viewed across age and geography.
Nature, 486(7402):222-7, 5 2012.
Jeong K, Nguyen V, and Kim J.
Human milk oligosaccharides: the novel modulator of intestinal microbiota.
BMB Rep, 45(8):433-41, 8 2012.
Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, and Gordon JI.
An obesity-associated gut microbiome with increased capacity for energy harvest.
Nature, 444(7122):1027-31, 12 2006.
Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, and Gordon JI.
A core gut microbiome in obese and lean twins.
Nature, 457(7228):480-4, 1 2009.
Kallus SJ and Brandt LJ.
The intestinal microbiota and obesity.
J Clin Gastroenterol, 46(1):16-24, 1 2012.
Claus SP, Ellero SL, Berger B, Krause L, Bruttin A, Molina J, Paris A, Want EJ, de Waziers I, Cloarec O, Richards SE, Wang Y, Dumas ME, Ross A, Rezzi S, Kochhar S, Van Bladeren P, Lindon JC, Holmes E, and Nicholson JK.
Colonization-induced host-gut microbial metabolic interaction.
MBio, 2(2):e00271-10, 3 2011.
Sczesnak A, Segata N, Qin X, Gevers D, Petrosino JF, Huttenhower C, Littman DR, Ivanov II, and Cell Host Microbe.
The genome of th17 cell-inducing segmented filamentous bacteria reveals extensive auxotrophy and adaptations to the intestinal environment.
Cell Host Microbe, 10(3):260-72, 9 2011.
Kriegel MA, Sefik E, Hill JA, Wu HJ, Benoist C, and Mathis D.
Naturally transmitted segmented filamentous bacteria segregate with diabetes protection in nonobese diabetic mice.
Proc Natl Acad Sci U S A, 108(28):11548-53, 7 2011.
Khoruts A and Sadowsky MJ.
Therapeutic transplantation of the distal gut microbiota.
Mucosal Immunol, 4(1):4-7, 1 2011.
Laparra JM and Sanz Y.
Interactions of gut microbiota with functional food components and nutraceuticals.
Pharmacol Res, 61(3):219-25, 3 2010.
Roberfroid M et al.
Prebiotic effects: metabolic and health benefits.
Br J Nutr, 104(Suppl 2):S1-63, 8 2010.
Mocali S and Benedetti A.
Exploring research frontiers in microbiology: the challenge of metagenomics in soil microbiology.
Res Microbiol, 161(6):497-505, Jul-Aug 2010.
Rajendhran J and Gunasekaran P.
Strategies for accessing soil metagenome for desired applications.
Biotechnol Adv, 26(6):576-90, Nov-Dec 2008.
van Elsas JD, Costa R, Jansson J, Sjöling S, Bailey M, Nalin R, Vogel TM, and van Overbeek L.
The metagenomics of disease-suppressive soils - experiences from the metacontrol project.
Trends Biotechnol, 26(11):591-601, 11 2008.
Reigstad LJ, Bartossek R, and Schleper C.
Preparation of high-molecular weight dna and metagenomic libraries from soils and hot springs.
Methods Enzymol, 496:319-44, 2011.
Mendes R, Kruijt M, de Bruijn I, Dekkers E, van der Voort M, Schneider JH, Piceno YM, Desantis TZ, Andersen GL, Bakker PA, and Raaijmakers JM.
Deciphering the rhizosphere microbiome for disease-suppressive bacteria.
Science, 10(33), 5 2011.
Hallam SJ Lee S.
Extraction of high molecular weight genomic dna from soils and sediments.
J Vis Exp, 10(33):pii:1569, 11 2009.
Orešič M, Hyötyläinen T, Herukka S-K, Sysi-Aho M, Mattila I, Seppänan-Laakso T, Julkunen V, Gopalacharyulu PV, Hallikainen M, Koikkalainen J, Kivipelto M, Helisalmi S, Lötjönen J, and Soininen H.
Metabolome in progression to alzheimer's disease.
Translational Psychiatry, 1:e57, 2011.
Li NJ, Liu WT, Li W, Li SQ, Chen XH, Bi KS, and He P.
Plasma metabolic profiling of alzheimer's disease by liquid chromatography/mass spectrometry.
Clin Biochem, 43(12):992-7, 8 2010.
Aminov RI and Mackie RI.
Evolution and ecology of antibiotic resistance genes.
FEMS Microbiol Lett, 27(2):147-61, 6 2007.
Forsberg KJ, Reyes A, Wang B, Selleck EM, Sommer MO, and Dantas G.
The shared antibiotic resistome of soil bacteria and human pathogens.
Science, 337(6098):1107-11, 8 2012.
Antibiotic resistance genes from the environment: a perspective through newly identified antibiotic resistance mechanisms in the clinical setting.
Clin Microbiol Infect, 15(Suppl 1):20-5, 1 2009.
The antibiotic resistome: the nexus of chemical and genetic diversity.
Nature Reviews Microbiology, 5:175-186, 3 2007.
Kyselková M, Chronáková A, Volná L, Nemec J, Ulmann V, Scharfen J, and Elhottová D.
Tetracycline resistance and presence of tetracycline resistance determinants (tet)(v) and (tap) in rapidly growing mycobacteria from agricultural soils and clinical isolates.
Microbes Environ, 5 2012.
See also: Related OurFood News
Copyright © 1998 - 2013 by K. H. Wilm - Impressum