Evolution of a genome-encoded bias in amino acid biosynthetic pathways is a potential indicator of amino acid dynamics in the environment.

Overcoming the stress of starvation is one of an organism's most challenging phenotypic responses. Those organisms that frequently survive the challenge, by virtue of their fitness, will have evolved genomes that are shaped by their specific environments. Understanding this genotype-environment-phenotype relationship at a deep level will require quantitative predictive models of the complex molecular systems that link these aspects of an organism's existence. Here, we treat one of the most fundamental molecular systems, protein synthesis, and the amino acid biosynthetic pathways involved in the stringent response to starvation. These systems face an inherent logical dilemma: Building an amino acid biosynthetic pathway to synthesize its product-the cognate amino acid of the pathway-may require that very amino acid when it is no longer available. To study this potential "catch-22," we have created a generic model of amino acid biosynthesis in response to sudden starvation. Our mathematical analysis and computational results indicate that there are two distinctly different outcomes: Partial recovery to a new steady state, or full system failure. Moreover, the cell's fate is dictated by the cognate bias, the number of cognate amino acids in the corresponding biosynthetic pathway relative to the average number of that amino acid in the proteome. We test these implications by analyzing the proteomes of over 1,800 sequenced microbes, which reveals statistically significant evidence of low cognate bias, a genetic trait that would avoid the biosynthetic quandary. Furthermore, these results suggest that the pattern of cognate bias, which is readily derived by genome sequencing, may provide evolutionary clues to an organism's natural environment

Unrelated toxin-antitoxin systems cooperate to induce persistence.

Persisters are drug-tolerant bacteria that account for the majority of bacterial infections. They are not mutants, rather, they are slow-growing cells in an otherwise normally growing population. It is known that the frequency of persisters in a population is correlated with the number of toxin-antitoxin systems in the organism. Our previous work provided a mechanistic link between the two by showing how multiple toxin-antitoxin systems, which are present in nearly all bacteria, can cooperate to induce bistable toxin concentrations that result in a heterogeneous population of slow- and fast-growing cells. As such, the slow-growing persisters are a bet-hedging subpopulation maintained under normal conditions. For technical reasons, the model assumed that the kinetic parameters of the various toxin-antitoxin systems in the cell are identical, but experimental data indicate that they differ, sometimes dramatically. Thus, a critical question remains: whether toxin-antitoxin systems from the diverse families, often found together in a cell, with significantly different kinetics, can cooperate in a similar manner. Here, we characterize the interaction of toxin-antitoxin systems from many families that are unrelated and kinetically diverse, and identify the essential determinant for their cooperation. The generic architecture of toxin-antitoxin systems provides the potential for bistability, and our results show that even when they do not exhibit bistability alone, unrelated systems can be coupled by the growth rate to create a strongly bistable, hysteretic switch between normal (fast-growing) and persistent (slow-growing) states. Different combinations of kinetic parameters can produce similar toxic switching thresholds, and the proximity of the thresholds is the primary determinant of bistability. Stochastic fluctuations can spontaneously switch all of the toxin-antitoxin systems in a cell at once. The spontaneous switch creates a heterogeneous population of growing and non-growing cells, typical of persisters, that exist under normal conditions, rather than only as an induced response. The frequency of persisters in the population can be tuned for a particular environmental niche by mixing and matching unrelated systems via mutation, horizontal gene transfer and selection

Elucidating the genotype-phenotype map by automatic enumeration and analysis of the phenotypic repertoire.

BackgroundThe gap between genotype and phenotype is filled by complex biochemical systems most of which are poorly understood. Because these systems are complex, it is widely appreciated that quantitative understanding can only be achieved with the aid of mathematical models. However, formulating models and measuring or estimating their numerous rate constants and binding constants is daunting. Here we present a strategy for automating difficult aspects of the process.MethodsThe strategy, based on a system design space methodology, is applied to a class of 16 designs for a synthetic gene oscillator that includes seven designs previously formulated on the basis of experimentally measured and estimated parameters.ResultsOur strategy provides four important innovations by automating: (1) enumeration of the repertoire of qualitatively distinct phenotypes for a system; (2) generation of parameter values for any particular phenotype; (3) simultaneous realization of parameter values for several phenotypes to aid visualization of transitions from one phenotype to another, in critical cases from functional to dysfunctional; and (4) identification of ensembles of phenotypes whose expression can be phased to achieve a specific sequence of functions for rationally engineering synthetic constructs. Our strategy, applied to the 16 designs, reproduced previous results and identified two additional designs capable of sustained oscillations that were previously missed.ConclusionsStarting with a system's relatively fixed aspects, its architectural features, our method enables automated analysis of nonlinear biochemical systems from a global perspective, without first specifying parameter values. The examples presented demonstrate the efficiency and power of this automated strategy

Design principles for elementary gene circuits: Elements, methods, and examples

The control of gene expression involves complex circuits that exhibit enormous variation in design. For years the most convenient explanation for these variations was historical accident. According to this view, evolution is a haphazard process in which many different designs are generated by chance; there are many ways to accomplish the same thing, and so no further meaning can be attached to such different but equivalent designs. In recent years a more satisfying explanation based on design principles has been found for at least certain aspects of gene circuitry. By design principle we mean a rule that characterizes some biological feature exhibited by a class of systems such that discovery of the rule allows one not only to understand known instances but also to predict new instances within the class. The central importance of gene regulation in modern molecular biology provides strong motivation to search for more of these underlying design principles. The search is in its infancy and there are undoubtedly many design principles that remain to be discovered. The focus of this three-part review will be the class of elementary gene circuits in bacteria. The first part reviews several elements of design that enter into the characterization of elementary gene circuits in prokaryotic organisms. Each of these elements exhibits a variety of realizations whose meaning is generally unclear. The second part reviews mathematical methods used to represent, analyze, and compare alternative designs. Emphasis is placed on particular methods that have been used successfully to identify design principles for elementary gene circuits. The third part reviews four design principles that make specific predictions regarding (1) two alternative modes of gene control, (2) three patterns of coupling gene expression in elementary circuits, (3) two types of switches in inducible gene circuits, and (4) the realizability of alternative gene circuits and their response to phased environmental cues. In each case, the predictions are supported by experimental evidence. These results are important for understanding the function, design, and evolution of elementary gene circuits. © 2001 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70891/2/CHAOEH-11-1-142-1.pd

The effect of medical students\u27 international experiences on attitudes toward serving underserved multicultural populations

BACKGROUND: We evaluated the effect of international electives on the attitudes of preclinical and clinical-year medical students with respect to serving underserved multicultural populations. METHODS: A self-assessment instrument was used to measure attitudes of 146 students before and after participating in international electives. The same attitudinal items were also analyzed at two time intervals for 18 students who completed international electives as preclinical students and 76 class cohorts who did not. RESULTS: Analyses show that the effect of international experiences is different for preclinical students and clinical students. For both groups, however, these experiences can develop and support perceptions and values conducive to serving underserved multicultural populations. These include reported increases in cultural competence and important personal attributes like idealism and enthusiasm. In addition, these experiences can heighten clarity about career roles, including those involving underserved multicultural patients. CONCLUSIONS: This study provides support for the hypothesis that international electives develop attributes that could benefit underserved multicultural populations

The effect of a global multiculturalism track on cultural competence of preclinical medical students

BACKGROUND: We evaluated the effect of an elective (the Global Multiculturalism Track), including international and domestic immersion experiences, on the cultural competence of preclinical medical students. METHODS: A self-assessment instrument was used to measure cultural competence, and it was administered to Track participants and nonparticipating class cohorts at the beginning and the end of the preclinical years. RESULTS: Track participants (n=26) had a higher level of cultural competence both at the beginning and at the end of the program. At the end of their second year, students participating in the Track had, for the first time, greater knowledge of certain aspects of local cultures, more tolerance of people of other cultures not speaking English, and more comfort with patients of these cultures, compared with non-Track participants. CONCLUSIONS: The results are based on a small sample size, but the suggestion that a multiculturalism track could provide a model for development of cultural competence warrants further research

Introduction to S-systems and the underlying power-law formalism

A novel approach to the development of an appropriate formalism for representing organizationally complex systems began in the mid 1960's with a search for a general systematic formalism that would retain the essential nonlinear features and that would still be amenable to mathematical analysis. The set of nonlinear differential equations that most closely approached this goal was called an "S-system", because it accurately captures the saturable and synergistic properties intrinsic to biological and other organizationally complex systems. In the early 1980's it was found that essentially any nonlinear differential equation composed of elementary functions could be recast exactly as an S-system. Thus, S-systems may be considered a canonical form with the ability to represent an enormous variety of nonlinear differential equations. This has given rise to new strategies for the mathematical modeling of nonlinear systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27576/1/0000620.pd