Welcome to the Walhout Lab

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The Structure, Function and Evolution of Biological Networks

The Walhout lab wishes to understand biological networks and how these networks adapt to different conditions. We use systems biology approaches to dissect these complex networks. These approaches combine high-quality and large-scale genetic and biochemical data sets and uses computational modeling to integrate the data such that the organizing principles and emergent properties of biological systems are unveiled.To examine biological networks we mainly use the model organism round worm Caenorhabditis elegans. Worms are highly adaptable, easy to manipulate, and have many analogs in human genetics. Furthermore, there are many genetic tools and worm-specific techniques that are not available for studying higher eukaryotes. Overall, our research involves two broad areas of biology:

1: Gene Regulatory Networks
2: Regulation of Metabolic Networks

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Transcriptional regulation of metabolic flux: a C. elegans perspective

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Metabolic reactions form the basis of life to generate biomass, produce energy and eliminate waste. Together, metabolic reactions function in the context of a highly interconnected metabolic network. Flux through this network needs to be adaptable depending on nutrient availability or metabolite buildup. Metabolic flux can be changed by different regulatory mechanisms, including the allosteric regulation of metabolic enzyme activity by small molecules, and by changes in metabolic gene expression. For the transcriptional control of metabolic genes to happen accurately, the metabolic status of the system needs to be relayed to the regulators of gene expression, such as transcription factors (TFs). While allosteric regulation of metabolic enzymes can only be studied for individual proteins, the transcriptional control of metabolism can increasingly be examined at a systems, or network level. Here, we discuss recent studies regarding the interplay between metabolic and gene regulatory networks using the nematode Caenorhabditis elegans. We discuss why C. elegans provides an elegant model system for studying the transcriptional regulation of metabolism and describe recent insights into its gene regulatory and metabolic networks. We then describe a recently discovered mechanism by which the buildup of a cellular metabolite can transcriptionally rewire metabolism. Finally, we discuss the future challenge of integrating large transcriptomic, proteomic and metabolomic datasets to fully understand the transcriptional regulation of metabolic flux.

Giese GE, Nanda S, Holdorf AD, Walhout AJM. (2019) Transcriptional regulation of metabolic flux: a C. elegans perspective. Curr Opin Syst Biol, In Press.

A Persistence Detector for Metabolic Network Rewiring in an Animal

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Highlights

  • A transcriptional persistence detector activates propionate shunt only when needed
  • Persistence detection prevents generation of toxic shunt intermediates
  • nhr-10 and nhr-68 are persistence detectors in a feed-forward loop with AND-logic gate
  • nhr-68 autoactivates and modeling shows that this can provide circuit tunability

Summary

Biological systems must possess mechanisms that prevent inappropriate responses to spurious environmental inputs. Caenorhabditis elegans has two breakdown pathways for the short-chain fatty acid propionate: a canonical, vitamin B12-dependent pathway and a propionate shunt that is used when vitamin B12 levels are low. The shunt pathway is kept off when there is sufficient flux through the canonical pathway, likely to avoid generating shunt-specific toxic intermediates. Here, we discovered a transcriptional regulatory circuit that activates shunt gene expression upon propionate buildup. Nuclear hormone receptor 10 (NHR-10) and NHR-68 function together as a “persistence detector” in a type 1, coherent feed-forward loop with an AND-logic gate to delay shunt activation upon propionate accumulation and to avoid spurious shunt activation in response to a non-sustained pulse of propionate. Together, our findings identify a persistence detector in an animal, which transcriptionally rewires propionate metabolism to maintain homeostasis.

Bulcha JT, Giese GE,Ali MZ, Lee Y-U, Walker MD, Holdorf AD, Yilmaz LS, Brewster RC, Walhout AJM. (2019) A Persistence Detector for Metabolic Network Rewiring in an Animal. Cell Reports 26, 460-468.

Perspective: If two deletions don’t stop growth, try three

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From Science, 360(6386), 269–270. Click to enlarge.

Dr. Walhout provides perspective in the April 20 issue of Science on the latest Research Article from a longstanding collaboration between Brenda Andrews and Charles Boone at the University of Toronto, and Chad Myers from the University of Minnesota. These groups constructed the first large scale trigenic interaction map of genes that affect colony growth in the yeast S. cerevisiae. The growth of these triple-deletion strains was compared with the growth of the strains harboring single or double deletions in the relevant genes. Given that a total of 36 billion potential trigenic interactions can occur in yeast, this study starts with a set of query strains carrying 302 single gene mutations and 151 double gene mutations. These query strains were tested for genetic interactions versus an array of 1182 strains, each carrying a mutation in an informative gene, so that most general biological processes were included. Thus, in total close to 200,000 trigenic interactions (∼0.0006% of all possible combinations) were tested. Dr. Walhout discusses the implications and future directions from the results of this study.

 

 

 

 

Perspective
Walhout AJM (2018). If two deletions don’t stop growth, try three. Science, 360(6386), 269–270.

Publication
Kuzmin E, VanderSluis B, Wang W, Tan G, Deshpande R, Chen Y, Usaj M, Balint A, Mattiazzi Usaj M, van Leeuwen J, Koch EN, Pons C, Dagilis AJ, Pryszlak M, Wang JZY, Hanchard J, Riggi M, Xu K, Heydari H, San Luis BJ, Shuteriqi E, Zhu H, Van Dyk N, Sharifpoor S, Costanzo M, Loewith R, Caudy A, Bolnick D, Brown GW, Andrews BJ, Boone C, Myers CL. (2018). Systematic analysis of complex genetic interactions. Science, 360(6386).

C. elegans MRP-5 Exports Vitamin B12 from Mother to Offspring to Support Embryonic Development

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Highlights
  • ABC transporter MRP-5 transports vitamin B12 from mother to offspring in C. elegans
  • mrp-5 mutant embryonic lethality is rescued by vitamin B12 injection into gonad
  • RNAi of mrp-5 reduces S-adenosylmethionine and methionine content in F1 embryos
Summary

Vitamin B12 functions as a cofactor for methionine synthase to produce the anabolic methyl donor S-adenosylmethionine (SAM) and for methylmalonyl-CoA mutase to catabolize the short-chain fatty acid propionate. In the nematode Caenorhabditis elegans, maternally supplied vitamin B12 is required for the development of offspring. However, the mechanism for exporting vitamin B12 from the mother to the offspring is not yet known. Here, we use RNAi of more than 200 transporters with a vitamin B12-sensor transgene to identify the ABC transporter MRP-5 as a candidate vitamin B12 exporter. We show that the injection of vitamin B12 into the gonad of mrp-5 deficient mothers rescues embryonic lethality in the offspring. Altogether, our findings identify a maternal mechanism for the transit of an essential vitamin to support the development of the next generation.

Huimin N, Ponomarova O, Giese GE, Walhout AJM. (2018). C. elegans MRP-5 Exports Vitamin B12 from Mother to Offspring to Support Embryonic Development. Cell Reports 22, 3126-3133.

Methods: Gateway Recombinational Cloning

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The January, 2018, issue of Cold Spring Harbor Protocols features three protocols on Gateway recombinatorial cloning for use in high-throughput studies.

The Gateway recombinatorial cloning system was developed for cloning multiple DNA fragments in parallel (e.g., in 96-well formats) in a standardized manner using the same enzymes. Gateway cloning is based on the highly specific integration and excision reactions of bacteriophage λ into and out of the Escherichia coli genome. Because the sites of recombination (“att” sites) are much longer (25–242 bp) than restriction sites, they are extremely unlikely to occur by chance in DNA fragments. Therefore, the same recombination enzyme can be used to robustly clone many different fragments of variable size in parallel reactions.

Reece-Hoyes JS, Walhout AJM. (2018) Gateway Recombinational Cloning. Cold Spring Harb. Protoc. 2018(1).

Introduction
Propagating Gateway Vectors
Generating an Open Reading Frame (ORF) Entry Clone and Destination Clone
Using Multisite LR Cloning to Generate a Destination Clone

Review: Worms, bugs and drugs: Caenorhabditis elegans as a model for host-microbe-drug interactions

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The microbiota plays a critical role in human health and disease. For instance, the gut microbiota aides in the digestion of foods, thereby contributing to our ability to metabolize compounds from our diet. Recently, it has become clear that the microbiota can also play an important role in the response to medications. However, several limitations in utilizing mammalian model systems, such as complex microbiota, high cost, and limited scalability, have constrained our ability to systematically test which bacteria affect the drug response and the mechanisms involved. The nematode Caenorhabditis elegans and its bacterial diet provide a facile interspecies model system to identify and characterize host-microbe-drug interactions. Two recent studies highlight the power of this model system. In brief, these studies identified two roles for bacteria in modulating the host drug response: (1) metabolic drug activation, and (2) supplementation of vitamins or nucleotides that affect the host’s drug response. This review will summarize the main findings of both studies, as well as provide some perspective into the advantages and limitations of the C. elegans-bacteria model for the detailed characterization of host-microbiota-drug interactions.

García-González AP, Walhout AJM (2017) Worms, bugs and drugs: Caenorhabditis elegans as a model for host-microbe-drug interactions. Curr. Opin. Sys. Biol. 6, 46-50.