Gilbert Jack A.

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Influence of acidic pH on hydrogen and acetate production by an electrosynthetic microbiome

(Public Library of Science, 2014-10-15) LaBelle, Edward V. ; Marshall, Christopher W. ; Gilbert, Jack A. ; May, Harold D.

Production of hydrogen and organic compounds by an electrosynthetic microbiome using electrodes and carbon dioxide as sole electron donor and carbon source, respectively, was examined after exposure to acidic pH (~5). Hydrogen production by biocathodes poised at −600 mV vs. SHE increased>100-fold and acetate production ceased at acidic pH, but ~5–15 mM (catholyte volume)/day acetate and>1,000 mM/day hydrogen were attained at pH ~6.5 following repeated exposure to acidic pH. Cyclic voltammetry revealed a 250 mV decrease in hydrogen overpotential and a maximum current density of 12.2 mA/cm2 at −765 mV (0.065 mA/cm2 sterile control at −800 mV) by the Acetobacterium-dominated community. Supplying −800 mV to the microbiome after repeated exposure to acidic pH resulted in up to 2.6 kg/m3/day hydrogen (≈2.6 gallons gasoline equivalent), 0.7 kg/m3/day formate, and 3.1 kg/m3/day acetate ( = 4.7 kg CO2 captured).
Current understanding of the human microbiome

( 2018-02-05) Gilbert, Jack A. ; Blaser, Martin J. ; Caporaso, J. Gregory ; Jansson, Janet K. ; Lynch, Susan V. ; Knight, Rob

Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this Review, we focus on studies in humans to describe these challenges, and propose strategies that leverage existing knowledge to move rapidly from correlation to causation, and ultimately to translation.
The microbiome-mitochondrion connection : common ancestries, common mechanisms, common goals

(American Society for Microbiology, 2017-05-09) Franco-Obregón, Alfredo ; Gilbert, Jack A.

Lynn Margulis in the 1960s elegantly proposed a shared phylogenetic history between bacteria and mitochondria; this relationship has since become a cornerstone of modern cellular biology. Yet, an interesting facet of the interaction between the microbiome and mitochondria has been mostly ignored, that of the systems biology relationship that underpins host health and longevity. The mitochondria are descendants of primordial aerobic pleomorphic bacteria (likely genus Rickettsia) that entered (literally and functionally) into a mutualistic partnership with ancient anaerobic microbes (likely Archaea). A stable symbiosis was established, given the metabolic versatility of the early mitochondria, which were capable of providing energy with or without oxygen, whereas nutrient gathering was the assumed responsibility of the host. While microbial relationships with single-cell protists must have occurred in the past, as they occur today, the evolution of multicellular organisms generated a new framework for symbiosis with the microbial world, taking the ancient partnership to an entirely new level. Cell-cell communication between microbes and single-cell protists was augmented through multicellularity to allow distant communication between the host cells and the microbiome, resulting in the development of complex metabolic relationships and an immune system to manage these interactions. Thus, the host is now the body and its resident mitochondria, and the microbiome is an essential supplier of metabolites that act at the level of mitochondria in skeletal muscle to stabilize host metabolism. We humans are caretakers of a profoundly vast and diverse microbiota, the majority of which resides in the gut. Indeed, the microbial genetic diversity of our microbiota outstrips our own by several orders of magnitude, and the cellular abundance is roughly equivalent to our somatic selves. Modern clinical science has elegantly highlighted the importance of the microbiome for metabolic health and well-being. This perspective underscores one fundamental facet of this symbiosis, the ancestral mitochondrion-microbiome axis.
Metatranscriptomics reveals temperature-driven functional changes in microbiome impacting cheese maturation rate

(Nature Publishing Group, 2016-02-25) De Filippis, Francesca ; Genovese, Alessandro ; Ferranti, Pasquale ; Gilbert, Jack A. ; Ercolini, Danilo

Traditional cheeses harbour complex microbial consortia that play an important role in shaping typical sensorial properties. However, the microbial metabolism is considered difficult to control. Microbial community succession and the related gene expression were analysed during ripening of a traditional Italian cheese, identifying parameters that could be modified to accelerate ripening. Afterwards, we modulated ripening conditions and observed consistent changes in microbial community structure and function. We provide concrete evidence of the essential contribution of non-starter lactic acid bacteria in ripening-related activities. An increase in the ripening temperature promoted the expression of genes related to proteolysis, lipolysis and amino acid/lipid catabolism and significantly increases the cheese maturation rate. Moreover, temperature-promoted microbial metabolisms were consistent with the metabolomic profiles of proteins and volatile organic compounds in the cheese. The results clearly indicate how processing-driven microbiome responses can be modulated in order to optimize production efficiency and product quality.
Toward interoperable bioscience data

(Nature Publishing Group, 2012-01-27) Sansone, Susanna-Assunta ; Rocca-Serra, Philippe ; Field, Dawn ; Maguire, Eamonn ; Taylor, Chris ; Hofmann, Oliver ; Fang, Hong ; Neumann, Steffen ; Tong, Weida ; Amaral-Zettler, Linda A. ; Begley, Kimberly ; Booth, Tim ; Bougueleret, Lydie ; Burns, Gully ; Chapman, Brad ; Clark, Tim ; Coleman, Lee-Ann ; Copeland, Jay ; Das, Sudeshna ; de Daruvar, Antoine ; de Matos, Paula ; Dix, Ian ; Edmunds, Scott ; Evelo, Chris T. ; Forster, Mark K. ; Gaudet, Pascale ; Gilbert, Jack A. ; Goble, Carole ; Griffin, Julian L. ; Jacob, Daniel ; Kleinjans, Jos ; Harland, Lee ; Haug, Kenneth ; Hermjakob, Henning ; Ho Sui, Shannan J. ; Laederach, Alain ; Liang, Shaoguang ; Marshall, Stephen ; McGrath, Annette ; Merrill, Emily ; Reilly, Dorothy ; Roux, Magali ; Shamu, Caroline E. ; Shang, Catherine A. ; Steinbeck, Christoph ; Trefethen, Anne ; Williams-Jones, Bryn ; Wolstencroft, Katherine ; Xenarios, Ioannis ; Hide, Winston

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.
Genomic Standards Consortium projects

(Genomic Standards Consortium, 2014) Field, Dawn ; Sterk, Peter ; Kottmann, Renzo ; De Smet, Wim ; Amaral-Zettler, Linda A. ; Cochrane, Guy R. ; James, Cole R. ; Davies, Neil ; Dawyndt, Peter ; Garrity, George M. ; Gilbert, Jack A. ; Glockner, Frank Oliver ; Hirschman, Lynette ; Klenk, Hans-Peter ; Knight, Rob ; Kyrpides, Nikos C. ; Meyer, Folker ; Karsch-Mizrachi, Ilene ; Morrison, Norman ; Robbins, Robert J. ; San Gil, Inigo ; Sansone, Susanna-Assunta ; Schriml, Lynn M. ; Tatusova, Tatiana ; Ussery, David W. ; Yilmaz, Pelin ; White, Owen ; Wooley, John ; Caporaso, J. Gregory

The Genomic Standards Consortium (GSC) is an open-membership community working towards the development, implementation and harmonization of standards in the field of genomics. The mission of the GSC is to improve digital descriptions of genomes, metagenomes and gene marker sequences. The GSC started in late 2005 with the defined task of establishing what is now termed the “Minimum Information about any Sequence” (MIxS) standard [1,2]. As an outgrowth of the activities surrounding the creation and implementation of the MixS standard there are now 18 projects within the GSC [3]. These efforts cover an ever widening range of standardization activities. Given the growth of projects and to promote transparency, participation and adoption the GSC has developed a “GSC Project Description Template”. A complete set of GSC Project Descriptions and the template are available on the GSC website. The GSC has an open policy of participation and continues to welcome new efforts. Any projects that facilitate the standard descriptions and exchange of data are potential candidates for inclusion under the GSC umbrella. Areas that expand the scope of the GSC are encouraged. Through these collective activities we hope to help foster the growth of the ‘bioinformatics standards’ community. For more information on the GSC and its range of projects, please see http://gensc.org/.
Introducing the microbiome into Precision Medicine

( 2016-11) Kuntz, Thomas M. ; Gilbert, Jack A.

Understanding how individual people respond to medical therapy is a key facet of improving the odds ratio that interventions will have a positive impact. Reducing the non-responder rate for an intervention or reducing complications associated with a particular treatment or surgery is the next stage of medical advance. The Precision Medicine Initiative, launched in January 2015, set the stage for enhanced collaboration between researchers and medical professionals to develop next-generation techniques to aid patient treatment and recovery, and increased the opportunities for impactful pre-emptive care. The microbiome plays a crucial role in health and disease, as it influences endocrinology, physiology, and even neurology, altering the outcome of many different disease states, and it augments drug responses and tolerance. We review the implications of the microbiome on precision health initiatives and highlight excellent examples, whereby precision microbiome health has been implemented.
Stool consistency as a major confounding factor affecting microbiota composition : an ignored variable?

( 2015-06) Gilbert, Jack A. ; Alverdy, John C.
Wheat rhizosphere harbors a less complex and more stable microbial co-occurrence pattern than bulk soil

( 2018-07-25) Fan, Kunkun ; Weisenhorn, Pamela B. ; Gilbert, Jack A. ; Chu, Haiyan

The rhizosphere harbors complex microbial communities, whose dynamic associations are considered critical for plant growth and health but remain poorly understood. We constructed co-occurrence networks for archaeal, bacterial and fungal communities associated with the rhizosphere and bulk soil of wheat fields on the North China Plain. Rhizosphere co-occurrence networks had fewer nodes, edges, modules and lower density, but maintained more robust structure compared with bulk soil, suggesting that a less complex topology and more stable co-occurrence pattern is a feature for wheat rhizosphere. Bacterial and fungal communities followed a power-law distribution, while the archaeal community did not. Soil pH and microbial diversity were significantly correlated with network size and connectivity in both rhizosphere and bulk soils. Keystone species that played essential roles in network structure were predicted to maintain a flexible generalist metabolism, and had fewer significant correlations with environmental variables, especially in the rhizosphere. These results indicate that distinct microbial co-occurrence patterns exist in wheat rhizosphere, which could be associated with variable agricultural ecosystem properties.
A simple novel device for air sampling by electrokinetic capture

(BioMed Central, 2015-12-27) Gordon, Julian ; Gandhi, Prasanthi ; Shekhawat, Gajendra ; Frazier, Angel ; Hampton-Marcell, Jarrad T. ; Gilbert, Jack A.

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrode assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87 %, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. The performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.
RCN4GSC Workshop Report : managing data at the interface of biodiversity and (meta)genomics, March 2011

(Genomic Standards Consortium, 2012-07-28) Robbins, Robert J. ; Amaral-Zettler, Linda A. ; Bik, Holly M. ; Blum, Stan D. ; Edwards, James ; Field, Dawn ; Garrity, George M. ; Gilbert, Jack A. ; Kottmann, Renzo ; Krishtalka, Leonard ; Lapp, Hilmar ; Lawrence, Carolyn ; Morrison, Norman ; O Tuama, Eamonn ; Parr, Cynthia Sims ; San Gil, Inigo ; Schindel, David ; Schriml, Lynn M. ; Vieglas, David ; Wooley, John

Building on the planning efforts of the RCN4GSC project, a workshop was convened in San Diego to bring together experts from genomics and metagenomics, biodiversity, ecology, and bioinformatics with the charge to identify potential for positive interactions and progress, especially building on successes at establishing data standards by the GSC and by the biodiversity and ecological communities. Until recently, the contribution of microbial life to the biomass and biodiversity of the biosphere was largely overlooked (because it was resistant to systematic study). Now, emerging genomic and metagenomic tools are making investigation possible. Initial research findings suggest that major advances are in the offing. Although different research communities share some overlapping concepts and traditions, they differ significantly in sampling approaches, vocabularies and workflows. Likewise, their definitions of ‘fitness for use’ for data differ significantly, as this concept stems from the specific research questions of most importance in the different fields. Nevertheless, there is little doubt that there is much to be gained from greater coordination and integration. As a first step toward interoperability of the information systems used by the different communities, participants agreed to conduct a case study on two of the leading data standards from the two formerly disparate fields: (a) GSC’s standard checklists for genomics and metagenomics and (b) TDWG’s Darwin Core standard, used primarily in taxonomy and systematic biology.
Predicting ecosystem emergent properties at multiple scales

( 2014-09) Gilbert, Jack A. ; Henry, Chris

Biological phenomena at the microbial community level encode information about the subpopulation of cells and taxa at a specific time in the succession and biogeochemical evolution of that assemblage. To capture and understand the entire population for a community at a temporal resolution at which biogeochemical processes influence geological climate dynamics, requires large-scale computational simulations of their formation and evolution. The interactions between components of biology, geochemistry and physical processes within an ecosystem are inherently non-linear, with complex feedback mechanisms. However, this complexity does not preclude quantification of the dynamics that govern the relationships. As such, if we understand the component dynamics at a given scale then prediction of their influences will be feasible, allowing for appropriate simulation of their response to shifts in system properties. While theorizing and experimentation are the most appropriate means of elucidating biological truth in ecological dynamics; simulation, especially for microbial communities, represents a new frontier for designing in silico experiments to test fundamental hypotheses. These can, by definition then be tested through observation, experimental manipulation and theory.
Recovering complete and draft population genomes from metagenome datasets

(BioMed Central, 2016-03-08) Sangwan, Naseer ; Xia, Fangfang ; Gilbert, Jack A.

Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem of chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.
The obese gut microbiome across the epidemiologic transition

(BioMed Central, 2016-01-11) Dugas, Lara R. ; Fuller, Miles ; Gilbert, Jack A. ; Layden, Brian T.

The obesity epidemic has emerged over the past few decades and is thought to be a result of both genetic and environmental factors. A newly identified factor, the gut microbiota, which is a bacterial ecosystem residing within the gastrointestinal tract of humans, has now been implicated in the obesity epidemic. Importantly, this bacterial community is impacted by external environmental factors through a variety of undefined mechanisms. We focus this review on how the external environment may impact the gut microbiota by considering, the host’s geographic location ‘human geography’, and behavioral factors (diet and physical activity). Moreover, we explore the relationship between the gut microbiota and obesity with these external factors. And finally, we highlight here how an epidemiologic model can be utilized to elucidate causal relationships between the gut microbiota and external environment independently and collectively, and how this will help further define this important new factor in the obesity epidemic.
Introducing the JMBE themed issue on scientific citizenship

(American Society for Microbiology, 2016-03) Gilbert, Jack A. ; Klyczek, Karen K. ; Elliott, Samantha L.

In this Editorial, the three Guest Editors for JMBE's first standalone themed issue introduce the topic of scientific citizenship and provide an overview of the current ideas and best practices contained within the issue.
Existing climate change will lead to pronounced shifts in the diversity of soil prokaryotes

(American Society for Microbiology, 2018-10-23) Ladau, Joshua ; Shi, Yu ; Jing, Xin ; He, Jin-Sheng ; Chen, Litong ; Lin, Xiangui ; Fierer, Noah ; Gilbert, Jack A. ; Pollard, Katherine ; Chu, Haiyan

Soil bacteria are key to ecosystem function and maintenance of soil fertility. Leveraging associations of current geographic distributions of bacteria with historic climate, we predict that soil bacterial diversity will increase across the majority (∼75%) of the Tibetan Plateau and northern North America if bacterial communities equilibrate with existing climatic conditions. This prediction is possible because the current distributions of soil bacteria have stronger correlations with climate from ∼50 years ago than with current climate. This lag is likely associated with the time it takes for soil properties to adjust to changes in climate. The predicted changes are location specific and differ across bacterial taxa, including some bacteria that are predicted to have reductions in their distributions. These findings illuminate the widespread potential of climate change to influence belowground diversity and the importance of considering bacterial communities when assessing climate impacts on terrestrial ecosystems.
Meeting report : Ocean ‘omics science, technology and cyberinfrastructure : current challenges and future requirements (August 20-23, 2013)

(Genomic Standards Consortium, 2014) Gilbert, Jack A. ; Dick, Gregory J. ; Jenkins, Bethany D. ; Heidelberg, John F. ; Allen, Eric E. ; Mackey, Katherine R. M. ; DeLong, Edward F.

The National Science Foundation’s EarthCube End User Workshop was held at USC’s Wrigley Marine Science Center on Catalina Island, California in August 2013. The workshop was designed to explore and characterise the needs and tools available to the community focusing on microbial and physical oceanography research with a particular focus on ‘omic research. The assembled researchers outlined the existing concerns regarding the vast data resources that are being generated, and how we will deal with these resources as their volume and diversity increases. Particular attention was focused on the tools for handling and analysing the existing data, and on the need for the construction and curation of diverse federated databases, as well as development of shared interoperable, “big-data capable” analytical tools. The key outputs from this workshop include (i) critical scientific challenges and cyberinfrastructure constraints, (ii) the current and future ocean ‘omics science grand challenges and questions, and (iii) data management, analytical and associated and cyber-infrastructure capabilities required to meet critical current and future scientific challenges. The main thrust of the meeting and the outcome of this report is a definition of the ‘omics tools, technologies and infrastructures that facilitate continued advance in ocean science biology, marine biogeochemistry, and biological oceanography.
Athletic equipment microbiota are shaped by interactions with human skin

(BioMed Central, 2015-06-19) Wood, Mariah ; Gibbons, Sean M. ; Lax, Simon ; Eshoo-Anton, Tifani W. ; Owens, Sarah M. ; Kennedy, Suzanne ; Gilbert, Jack A. ; Hampton-Marcell, Jarrad T.

Americans spend the vast majority of their lives in built environments. Even traditionally outdoor pursuits, such as exercising, are often now performed indoors. Bacteria that colonize these indoor ecosystems are primarily derived from the human microbiome. The modes of human interaction with indoor surfaces and the physical conditions associated with each surface type determine the steady-state ecology of the microbial community. Bacterial assemblages associated with different surfaces in three athletic facilities, including floors, mats, benches, free weights, and elliptical handles, were sampled every other hour (8 am to 6 pm) for 2 days. Surface and equipment type had a stronger influence on bacterial community composition than the facility in which they were housed. Surfaces that were primarily in contact with human skin exhibited highly dynamic bacterial community composition and non-random co-occurrence patterns, suggesting that different host microbiomes—shaped by selective forces—were being deposited on these surfaces through time. However, bacterial assemblages found on the floors and mats changed less over time, and species co-occurrence patterns appeared random, suggesting more neutral community assembly. These longitudinal patterns highlight the dramatic turnover of microbial communities on surfaces in regular contact with human skin. By uncovering these longitudinal patterns, this study promotes a better understanding of microbe-human interactions within the built environment.
Satellite remote sensing data can be used to model marine microbial metabolite turnover

(Nature Publishing Group, 2014-07-29) Larsen, Peter E. ; Scott, Nicole ; Post, Anton F. ; Field, Dawn ; Knight, Rob ; Hamada, Yuki ; Gilbert, Jack A.

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.
The taxonomic and functional diversity of microbes at a temperate coastal site : a ‘multi-omic’ study of seasonal and diel temporal variation

(Public Library of Science, 2010-11-29) Gilbert, Jack A. ; Field, Dawn ; Swift, Paul ; Thomas, Simon ; Cummings, Denise ; Temperton, Ben ; Weynberg, Karen ; Huse, Susan M. ; Hughes, Margaret ; Joint, Ian ; Somerfield, Paul J. ; Muhling, Martin

How microbial communities change over time in response to the environment is poorly understood. Previously a six-year time series of 16S rRNA V6 data from the Western English Channel demonstrated robust seasonal structure within the bacterial community, with diversity negatively correlated with day-length. Here we determine whether metagenomes and metatranscriptomes follow similar patterns. We generated 16S rRNA datasets, metagenomes (1.2 GB) and metatranscriptomes (157 MB) for eight additional time points sampled in 2008, representing three seasons (Winter, Spring, Summer) and including day and night samples. This is the first microbial ‘multi-omic’ study to combine 16S rRNA amplicon sequencing with metagenomic and metatranscriptomic profiling. Five main conclusions can be drawn from analysis of these data: 1) Archaea follow the same seasonal patterns as Bacteria, but show lower relative diversity; 2) Higher 16S rRNA diversity also reflects a higher diversity of transcripts; 3) Diversity is highest in winter and at night; 4) Community-level changes in 16S-based diversity and metagenomic profiles are better explained by seasonal patterns (with samples closest in time being most similar), while metatranscriptomic profiles are better explained by diel patterns and shifts in particular categories (i.e., functional groups) of genes; 5) Changes in key genes occur among seasons and between day and night (i.e., photosynthesis); but these samples contain large numbers of orphan genes without known homologues and it is these unknown gene sets that appear to contribute most towards defining the differences observed between times. Despite the huge diversity of these microbial communities, there are clear signs of predictable patterns and detectable stability over time. Renewed and intensified efforts are required to reveal fundamental deterministic patterns in the most complex microbial communities. Further, the presence of a substantial proportion of orphan sequences underscores the need to determine the gene products of sequences with currently unknown function.

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