Biology subjects

Ogbunugafor, C. B.

Publications and source records attributed to Ogbunugafor, C. B..

23 records · Page 2Linked to original sources

bioRxiv2019

Deconstructing higher-order interactions in the microbiota: A theoretical examination

O_LIA major objective of microbial ecology is to identify how the composition of gut microbial taxa shapes host phenotypes. However, most studies focus solely on community-level patterns and pairwise interactions and ignore the potentially significant effects of higher-order interactions involving three or more component taxa. C_LIO_LIStudies on higher-order interactions among microbial taxa are scarce for many reasons, including experimental intractability, daunting diversity and complexity of many microbial systems, and the potential confounding role of the environment. Moreover, we still lack the empirical and statistical tools to isolate and understand the role of higher-order interactions on the host. C_LIO_LIHere, we apply a mathematical approach to quantifying the effects of higher-order interactions among taxa on host infection risk. To do so, we adapt the Hadamard-Walsh method recently used in evolutionary genetics to quantify the nonlinear effects of mutations on fitness. We apply our approach to an in silico dataset built to resemble a population of insect hosts with gut-associated microbial communities at risk of infection from an intestinal parasite. Critically, we examine these interactions across a breadth of environmental contexts, using nutrient content of the insect diet as a model for context. C_LIO_LIWe find that the effect of higher-order interactions is considerable and can change appreciably across environmental contexts. Strikingly, the relative eminence of different orders (pairwise vs. third order, fourth order, and fifth order) changes as a function of environmental context. Furthermore, we show-in our theoretical microcosm-that higher-order interactions can stabilize community structure thereby reducing host susceptibility to parasite invasion. C_LIO_LIOur approach illustrates how incorporating the effects of higher-order interactions among gut microbiota across environments can be essential for understanding their effects on host phenotypes. We conclude that higher-order interactions among taxa can profoundly shape important organismal phenotypes, and they deserve greater attention in host-associated microbiome studies. C_LI

ecology↗

bioRxiv2019

Lexical landscapes as large in silico data forexamining advanced properties of fitness landscapes

In silico approaches have served a central role in the development of evolutionary theory for generations. This especially applies to the concept of the fitness landscape, one of the most important abstractions in evolutionary genetics, and one which has benefited from the presence of large empirical data sets only in the last decade or so. In this study, we propose a method that allows us to generate enormous data sets that walk the line between in silico and empirical: word usage frequencies as catalogued by the Google ngram corpora. These data can be codified or analogized in terms of a multidimensional empirical fitness landscape towards the examination of advanced concepts--adaptive landscape by environment interactions, clonal competition, higher-order epistasis and countless others. We argue that the greater Lexical Landscapes approach can serve as a platform that offers an astronomical number of fitness landscapes for exploration (at least) or theoretical formalism (potentially) in evolutionary biology.

evolutionary biology↗

bioRxiv2019

Waterborne, abiotic and other indirectly transmitted (W.A.I.T.) infections are defined by the dynamics of free-living pathogens and environmental reservoirs

While the ecology of infectious disease is a rich field with decades worth of empirical evidence and theory, there are aspects that remain relatively under-examined. One example is the importance of the free-living survival stage of certain pathogens, and especially is cases where they are transmitted indirectly between hosts through an environmental reservoir intermediate. In this study, we develop an integrated, broadly applicable mathematical method to examine diseases fitting this description--the waterborne, abiotic and other indirectly transmitted (W.A.I.T.) infection framework. To demonstrate its utility, we construct realistic models of two very different epidemic scenarios: cholera in a densely populated setting with limited access to clean drinking water and hepatitis C virus in an urban setting of injection-drug users. Using these two exemplars, we find that the W.A.I.T. model fortifies the centrality of reservoir dynamics in the "sit and wait" infection strategy, and provides a way to simulate a diverse set of intervention strategies.

systems biology↗

bioRxiv2018

Proteostasis environment shapes higher-order epistasis operating on antibiotic resistance

Recent studies have shown that higher-order epistasis is ubiquitous and can have large effects on complex traits. Yet, we lack frameworks for understanding how epistatic interactions are influenced by basic aspects of cell physiology. In this study, we assess how protein quality control machinery--a critical component of cell physiology--affects epistasis for different traits related to bacterial resistance to antibiotics. Specifically, we attempt to disentangle the interactions between different protein quality control genetic backgrounds and two sets of mutations: (i) SNPs associated with resistance to antibiotics in an essential bacterial enzyme (dihydrofolate reductase, or DHFR) and (ii) differing DHFR bacterial species-specific amino acid background sequences (Escherichia coli, Listeria grayi, and Chlamydia muridarum). In doing so, we add nuance to the generic observation that non-linear genetic interactions are widespread and capricious in nature, by proposing a mechanistically-grounded analysis of how proteostasis shapes epistasis. These findings simultaneously fortify and demystify the role of environmental context in modulating higher-order epistasis, with direct implications for evolutionary theory, genetic modification technology, and efforts to manage antimicrobial resistance.

genetics↗

bioRxiv2018

Genotypic context modulates fitness landscapes: Effects onthe speed and direction of evolution for antimicrobialresistance

Understanding the forces that drive the dynamics of adaptive evolution is a goal of many subfields within evolutionary biology. The fitness landscape analogy has served as a useful abstraction for addressing these topics across many systems, and recent treatments have revealed how different environments can frame the particulars of adaptive evolution by changing the topography of fitness landscapes. In this study, we examine how the larger, ambient genotypic context in which the fitness landscape being modeled is embedded affects fitness landscape topography and subsequent evolution. Using simulations on empirical fitness landscapes, we discover that genotypic context, defined by genetic variability in regions outside of the locus under study (in this case, an essential bacterial enzyme target of antibiotics), influences the speed and direction of evolution in several surprising ways. These findings have implications for how we study the evolution of drug resistance in nature, and for presumptions about how biological evolution might be expected to occur in genetically-modified organisms. More generally, the findings speak to theory surrounding how \"difference can beget difference\" in adaptive evolution: that small genetic differences between organisms can greatly alter the specifics of how evolution occurs, which can rapidly drive even slightly diverged populations further apart.\n\nAuthor summaryTechnological advances enable scientists to engineer individual mutations at specific sites within an organisms genome with increasing ease. These breakthroughs have provided scientists with tools to study how different engineered mutations affect the function of a given gene or protein, yielding useful insight into genotype-phenotype mapping and evolution. In this study, we use engineered strains of bacteria to show how the dynamics (speed and direction) of evolution of drug resistance in an enzyme depends on the species-type of that bacterial enzyme, and on the presence/absence of mutations in other genes in the bacterial genome. These findings have broad implications for public health, genetic engineering, and theories of speciation. In the context of public health and biomedicine, our results suggest that future efforts in managing antimicrobial resistance must consider genetic makeup of different pathogen populations before predicting how resistance will occur, rather than assuming that the same resistance pathways will appear in different pathogen populations. With regard to broader theory in evolutionary biology, our results show how even small genetic differences between organisms can alter how future evolution occurs, potentially causing closely-related populations to quickly diverge.

evolutionary biology↗