Resident microbes of the human body, particularly the gut microbiota, provide essential functions for the host, and, therefore, have important roles in human health as well as mitigating disease. It is difficult to study the mechanisms by which the microbiota affect human health, especially at a systems-level, due to heterogeneity of human genomes, the complexity and heterogeneity of the gut microbiota, the challenge of growing these bacteria in the laboratory, and the lack of bacterial genetics in most microbiotal species. In the last few years, the interspecies model of the nematode Caenorhabditis elegans and its bacterial diet has proven powerful for studying host–microbiota interactions, as both the animal and its bacterial diet can be subjected to large-scale and high-throughput genetic screening. The high level of homology between many C. elegans and human genes, as well as extensive similarities between human and C. elegans metabolism, indicates that the findings obtained from this interspecies model may be broadly relevant to understanding how the human microbiota affects physiology and disease. In this review, we summarize recent systems studies on how bacteria interact with C. elegans and affect life history traits.
Zhang J, Holdorf AD, Walhout AJ. (2017) C. elegans and its bacterial diet as a model for systems-level understanding of host–microbiota interactions. Curr. Opin. Biotechnol. 46, 74-80.
Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions.
An important question when studying gene regulation is which transcription factors (TFs) interact with which cis-regulatory elements, such as promoters and enhancers. Addressing this issue in complex multicellular organisms is challenging as several hundreds of TFs and thousands of regulatory elements must be considered in the context of different tissues and physiological conditions. Yeast one-hybrid (Y1H) assays provide a powerful “gene-centered” method to identify the TFs that can bind a DNA sequence of interest. In this introduction, we describe the basic principles of the Y1H assay and its advantages and disadvantages and briefly discuss how it is complementary to “TF-centered” methods that identify protein-DNA interactions for a known protein of interest.
Fuxman Bass JI, Reece-Hoyes JS, Walhout AJ. (2016). Gene-Centered Yeast One-Hybrid Assays. Cold Spring Harb. Prot., 2016(12).
TF–cofactor protein–protein interaction network from Reece‐Hoyes et al (2013) was used to predict activators and repressors. Blue, predicted repressors; red, predicted activators; yellow, cofactors; blue outline, co‐repressors; red outline, co‐activators.
Transcription factors (TFs) play a central role in controlling spatiotemporal gene expression and the response to environmental cues. A comprehensive understanding of gene regulation requires integrating physical protein–DNA interactions (PDIs) with TF regulatory activity, expression patterns, and phenotypic data. Although great progress has been made in mapping PDIs using chromatin immunoprecipitation, these studies have only characterized ~10% of TFs in any metazoan species. The nematode C. elegans has been widely used to study gene regulation due to its compact genome with short regulatory sequences. Here, we delineated the largest gene‐centered metazoan PDI network to date by examining interactions between 90% of C. elegans TFs and 15% of gene promoters. We used this network as a backbone to predict TF binding sites for 77 TFs, two‐thirds of which are novel, as well as integrate gene expression, protein–protein interaction, and phenotypic data to predict regulatory and biological functions for multiple genes and TFs.
Fuxman Bass, JI, Pons, C, Kozlowski, L, Reece‐Hoyes, JS, Shrestha, S, Holdorf, AD, Mori, A, Myers, CL, Walhout, AJM. (2016). A gene‐centered C. elegans protein–DNA interaction network provides a framework for functional predictions. Mol. Sys. Biol. 12: 884. doi: 10.15252/msb.20167131
Best wishes to Dr. Juan Fuxman Bass who has left the lab to start his own lab as an Assistant Professor in the Department of Biology at Boston University. He will be working on transcription factors that regulate the immune response. We will miss you Juan!
The Walhout lab participated in the annual joint Cancer Center for Systems Biology (CCSB) and Program in Systems Biology (PSB) retreat in Gloucester, MA, on September 7-9. The retreat attendees heard talks from their colleagues in CCSB and PSB, as well as lectures form other invited speakers. Distinguished Professor John Roth of UC Davis opened the retreat with a historical perspective of his work on mutation selection in bacteria. University of Toronto Professor and Howard Hughes Medical Institute Senior International Research Scholar Charlie Boone presented the keynote lecture on genetic networks in yeast, and Tufts University Professor and Howard Hughes Medical Institute Professor David Walt discussed how basic science research lead to the co-founding of the company Illumina. Walhout lab post-doctoral fellows Jingyan Zhang and Huimin Na, and graduate student Aurian Garcia-Gonzalez all gave short talks about their exciting research on C. elegans networks.
Metabolic network rewiring is the rerouting of metabolism through the use of alternate enzymes to adjust pathway flux and accomplish specific anabolic or catabolic objectives. Here, we report the first characterization of two parallel pathways for the breakdown of the short chain fatty acid propionate in Caenorhabditis elegans. Using genetic interaction mapping, gene co-expression analysis, pathway intermediate quantification and carbon tracing, we uncover a vitamin B12-independent propionate breakdown shunt that is transcriptionally activated on vitamin B12 deficient diets, or under genetic conditions mimicking the human diseases propionic- and methylmalonic acidemia, in which the canonical B12-dependent propionate breakdown pathway is blocked. Our study presents the first example of transcriptional vitamin-directed metabolic network rewiring to promote survival under vitamin deficiency. The ability to reroute propionate breakdown according to B12 availability may provide C. elegans with metabolic plasticity and thus a selective advantage on different diets in the wild.
Watson E, Olin-Sandoval V, Hoy MJ, Li C, Louisse T, Yao V, Mori A, Holdorf AD, Troyanskaya OG, Ralser M, Walhout AJM (2016) Metabolic network rewiring of propionate flux compensates vitamin B12 deficiency in C. elegans. eLife, doi: 10.7554/eLife.17670