Supreet Saini - Academia.edu (original) (raw)
Papers by Supreet Saini
Frontiers in Ecology and Evolution
One of the central goals of ecology is to explain and predict coexistence of species. In this con... more One of the central goals of ecology is to explain and predict coexistence of species. In this context, microbial communities provide a model system where community structure can be studied in environmental niches and in laboratory conditions. A community of microbial population is stabilized by interactions between participating species. However, the nature of these stabilizing interactions has remained largely unknown. Theory and experiments have suggested that communities are stabilized by antagonistic interactions between member species, and destabilized by synergistic interactions. However, experiments have also revealed that a large fraction of all the interactions between species in a community are synergistic in nature. To understand the relative significance of the two types of interactions (synergistic vs. antagonistic) between species, we perform simulations of microbial communities with a small number of participating species using two frameworks—a replicator equation and...
Power flow analysis stands out as the foundation of power system preliminary research as well as ... more Power flow analysis stands out as the foundation of power system preliminary research as well as design. They are really essential for planning, operation, economic scheduling and interchange of power between utilities. The primary facts concerning power flow analysis are to identify the magnitude and phase angle of the voltage at every single bus and the real and reactive power flowing in each transmission system lines. The load flow study in a power system comprises a study of extremely important significance. The analysis uncovers the electrical performance and power flows (real and reactive) for stipulated circumstances whenever the system is functioning under the consistent state. This paper gives an overview of various techniques useful for load flow study under distinctive stipulated conditions.
Figure S1. The likelihood of reaching global optima increases from zero to one around critical va... more Figure S1. The likelihood of reaching global optima increases from zero to one around critical value of K when the benefit is higher than the cost. In this simulation the parameter (A) a is increased by a factor of 10; (B) parameter associated with cost per protein molecules (Îą) is increased by a factor of 10; (C) the parameter associated the sensitivity of the benefit function (b) is increased by a factor of 10; and (D) the parameter associated the sensitivity of the benefit function (b) is decreased by a factor of 10. Table S1. Parameter range of all 6 parameters (k, kr, kd, b, km, bas) used in the simulations. (DOCX 503 kb)
Frontiers in Microbiology
Environmental cues in an ecological niche are often temporal in nature. For instance, in temperat... more Environmental cues in an ecological niche are often temporal in nature. For instance, in temperate climates, temperature is higher in daytime compared to during night. In response to these temporal cues, bacteria have been known to exhibit anticipatory regulation, whereby triggering response to a yet to appear cue. Such an anticipatory response in known to enhance Darwinian fitness, and hence, is likely an important feature of regulatory networks in microorganisms. However, the conditions under which an anticipatory response evolves as an adaptive response are not known. In this work, we develop a quantitative model to study response of a population to two temporal environmental cues, and predict variables which are likely important for evolution of anticipatory regulatory response. We follow this with experimental evolution of Escherichia coli in alternating environments of rhamnose and paraquat for ∼850 generations. We demonstrate that growth in this cyclical environment leads to ...
Adaptive diversification of an isogenic population, and its molecular basis has been a subject of... more Adaptive diversification of an isogenic population, and its molecular basis has been a subject of a number of studies in the last few years. Microbial populations offer a relatively convenient model system to study this question. In this context, an isogenic population of bacteria (E. coli, B. subtilis, and Pseudomonas) has been shown to lead to genetic diversification in the population, when propagated for a number of generations. This diversification is known to occur when the individuals in the population have access to two or more resources/environments, which are separated either temporally or spatially. Here, we report adaptive diversification in an isogenic population of yeast, S. cerevisiae, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good, enzyme α-galactosidase, leading to hydrolysis of melibiose into two distinct resources, glucose and galactose. The diversification is driven by a mutations at ...
Mutations provide the raw material for natural selection to act. Therefore, understanding the var... more Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments performed with organisms such asDrosophilahave an effective population size of one. However, in MA experiments with bacteria and yeast, a single founder is allowed to grow to a size of a colony (~108). The effective population size in these experiments is of the order of 10. In this scenario, while it is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth and therefore, the MA experiment; this effect has not been tested explicitly. In this work, we simulate colony growth and perform an MA experiment, and demonstrate...
mSystems
Cooperative behaviors are highly prevalent in the wild, but their evolution is not understood. Me... more Cooperative behaviors are highly prevalent in the wild, but their evolution is not understood. Metabolic flux models can demonstrate the viability of metabolic exchange as cooperative interactions, but steady-state growth models cannot explain why cooperators grow faster.
Frontiers in Genetics
Heterogeneity among isogenic cells/individuals has been known for at least 150 years. Even Mendel... more Heterogeneity among isogenic cells/individuals has been known for at least 150 years. Even Mendel, working on pea plants, realized that not all tall plants were identical. However, Mendel was more interested in the discontinuous variation between genetically distinct individuals. The concept of environment dictating distinct phenotypes among isogenic individuals has since been shown to impact the evolution of populations in numerous examples at different scales of life. In this review, we discuss how phenotypic heterogeneity and its evolutionary implications exist at all levels of life, from viruses to mammals. In particular, we discuss how a particular disease condition (cancer) is impacted by heterogeneity among isogenic cells, and propose a potential role that phenotypic heterogeneity might play toward the onset of the disease.
Environmental cues in an ecological niche are temporal. In response to these temporal cues, bacte... more Environmental cues in an ecological niche are temporal. In response to these temporal cues, bacteria have been known to exhibit learning or conditioning, whereby they trigger response to a yet to appear cue, anticipating its actual arrival in the near future. Such an anticipatory response in known to enhance Darwinian fitness, and hence, is likely an important feature in the regulatory networks in microorganisms. However, the conditions under which an anticipatory response optimizes cellular fitness are not known. Nor has evolution of anticipatory regulation in laboratory conditions been experimentally demonstrated. In this work, we develop a quantitative model to study response of a population to two temporal environmental cues, and present the key variables in cellular physiology associated with response to the cues whose modulation is likely to lead to evolution of anticipatory regulatory response. We predict experimental conditions, which are likely to lead to demonstration of r...
The question of chance vs. determinism in dictating evolutionary trajectories has been a broad qu... more The question of chance vs. determinism in dictating evolutionary trajectories has been a broad question of interest in the last few decades. This question has not been addressed in the context of reverse evolution. By reverse evolution, we mean a scenario where selection is reversed. In this work, we use evolution of multicellularity in S. cerevisiae as a model to answer this question. When selected for fast-settling variants, multicellularity rapidly evolves in the organism. On reversing selection, unicellularity evolves from the multicellular clusters. However, the dynamic trajectories of the two processes are completely different. The molecular determinants dictating the two adaptive processes are also distinct from each other. In this context, evolution is not reversed dynamically or at a molecular level. The phenotypic reversal, however, is driven by epistatic interactions in the genome. How epistatic interactions evolve in a genome and shape evolutionary trajectories remains l...
Journal of the Indian Institute of Science
How Did It All Start Following Pasteur's discovery that yeast proliferates by fermenting glucose ... more How Did It All Start Following Pasteur's discovery that yeast proliferates by fermenting glucose to ethanol 1, 2 , Dienert observed that yeast exposed to glucose and galactose simultaneously, consumes glucose first and only when all the glucose in the media is exhausted, switches over to galactose 3. This phenomenon, rediscovered by Karstrome in bacteria 4 , gave birth to the concept of enzyme adaptation, where presence of the substrate drives the pre-existing equilibrium between inactive and active forms towards the active form 5. Monod,
Journal of the Indian Institute of Science
Introduction: Coordinated Behavior of Bacterial Populations Bacteria, when thought of with regard... more Introduction: Coordinated Behavior of Bacterial Populations Bacteria, when thought of with regards to their physiology and life cycle, are often viewed as single cells which make lifestyle decisions independent of their biological neighborhood. The physiological decisions made by this single cell are thought of as being driven solely towards the aim of increasing fitness of that particular individual bacterium. Therefore, bacteria were considered to live asocially with the sole of focus of maximizing chances of proliferation in a given environment. However, numerous ecological isolates reveal that bacteria rarely reside as a single species 1-4. Moreover, multiple species coexist and members from each are often interacting with each other. The most well studied niches in this context are intestines of mammals, biofilms on abiotic surfaces, or bacterial communities residing in soil. A study of physiology of bacteria residing in these niches suggests that bacteria residing here cooperate with each other, and this cooperation ensures maximization of fitness of the collective
Letters in Applied Microbiology
Bacteria frequently encounter multiple sugars in their natural surroundings. While the dynamics o... more Bacteria frequently encounter multiple sugars in their natural surroundings. While the dynamics of utilization of glucose‐containing sugar mixtures have been well investigated, there are few reports addressing regulation of utilization of glucose‐free mixtures particularly pentoses. These sugars comprise a considerable fraction in hemicellulose which can be converted by suitable biocatalysts to biofuels and other value‐added products. Hence, understanding of transcriptional cross‐regulation among different pentose sugar utilization systems is essential for successful development of industrial strains. In this work, we study mixed‐sugar utilization with respect to three secondary carbon sources — arabinose, xylose and rhamnose at single‐cell resolution in Escherichia coli. Our results reveal that hierarchical utilization among these systems is not strict but rather can be eliminated or reversed by altering the relative ratios of the preferred and nonpreferred sugars. Since transcriptional cross‐regulation among pentose sugar systems operates through competitive binding of noncognate sugar‐regulator complex, altering sugar concentrations is thought to eliminate nonspecific binding by affecting concentration of the regulator — sugar complexes.
The Canadian Journal of Chemical Engineering
Journal of Evolutionary Biology
Cellular energetics is thought to have played a key role in dictating all major evolutionary tran... more Cellular energetics is thought to have played a key role in dictating all major evolutionary transitions in the history of life on Earth. However, how exactly cellular energetics and metabolism come together to shape evolutionary paths is not well understood. In particular, when an organism is evolved in different energy environments, what are the phenomenological differences in the chosen evolutionary trajectories, is a question that is not well understood. In this context, starting from an Escherichia coli K‐12 strain, we evolve the bacterium in five different carbon environments—glucose, arabinose, xylose, rhamnose and a mixture of these four sugars (in a predefined ratio) for approximately 2,000 generations. At the end of the adaptation period, we quantify and compare the growth dynamics of the strains in a variety of environments. The evolved strains show no specialized adaptation towards growth in the carbon medium in which they were evolved. Rather, in all environments, the evolved strains exhibited a reduced lag phase and an increased growth rate. Sequencing results reveal that these dynamical properties are not introduced via mutations in the precise loci associated with utilization of the sugar in which the bacterium evolved. These phenotypic changes are rather likely introduced via mutations elsewhere on the genome. Data from our experiments indicate that evolution in a defined environment does not alter hierarchy in mixed‐sugar utilization in bacteria.
Starting from a parentalE. coliK-12 MG1655 strain, we evolve cells in five different carbon envir... more Starting from a parentalE. coliK-12 MG1655 strain, we evolve cells in five different carbon environments-glucose, arabinose, xylose, rhamnose, and a mixture of these four sugars (in a predefined ratio) for approximately 2,000 generations. At the end of the adaptation period, we quantify and compare growth dynamics of the strains in a variety of environments. The evolved strains show no specialized adaptation towards growth in the carbon medium in which they were evolved. Rather, in all environments, the evolved strains exhibited a reduced lag phase and an increased growth rate. Sequencing results reveal that these dynamical properties are not introduced via mutations in the precise loci associated with utilization of the sugar in which the bacterium was evolved in. These phenotypic changes are rather likely introduced via mutationselsewhere onthe genome. Sugar systems are known to exhibit hierarchy in utilization. Evolution in a defined environment, in our experimental framework, do...
Plasmodium parasite, a representative member of phylum Apicomplexa is a causative agent of malari... more Plasmodium parasite, a representative member of phylum Apicomplexa is a causative agent of malaria in human as well as other animals. To infect host cells, Plasmodium first finds receptors on the host cell surface, then binds specifically, and finally penetrates host cell membrane to acquire the host cellular resources. The motility for moving on the cell surface is equipped by the precise and tight control of actin treadmill. Several regulators are required to achieve precision and robustness in the control of actin treadmill. However, the mechanistic detail of the treadmill regulatory network and the cross-talk among regulators are not well understood. We developed a stochastic model of treadmill regulation and explored the dynamics of filament growth, nucleation time, and elongation time. Our study mainly highlighted on how and what helps cells to maintain an average size of the actin filaments within a species. This is particularly important, since, excessive growth of filament ...
Scientific Reports
demonstrated the first approach to estimate DFE, using Gillespie's mutational model, which uses E... more demonstrated the first approach to estimate DFE, using Gillespie's mutational model, which uses Extreme Value Theory to estimate that, statistically, beneficial mutations should be exponentially distributed 13. Satisfactory agreement with these predictions was found in a study where the authors study mutational effects in viruses 14. Subsequent approaches use statistical analysis applied on drosophila population data and human amino acid mutations (or SNPs), to estimate DFE of deleterious mutations 15-17. Approaches using population data assume that the present population is fitter with beneficial mutations enhanced in frequency, and thus, older variations must be lower in fitness. Minor variants that are declining in frequency are considered deleterious. The above approaches, either assume an abstract mutational model, or use existing dynamic population level data to estimate fitness effect sizes of mutations (Amino Acid variants or SNPs) in the populations. These help provide a general picture, but cannot capture the specific dynamics of a real biological system. These limitations motivated us to ask if it would be possible to obtain a specific fitness landscape and DFE of a biological system, derived from the mathematical model defined to functionally characterize the system. Such mathematical models of biological systems when tuned with experimentally derived parameter sets, have been extremely successful in describing the behaviour and dynamical properties of a number of systems 18,19. If these models truly capture the system's mechanistic dynamics, it is expected that it should also be able to predict the change in the system dynamics upon change in the system parameters by way of mutations, and hence give us a handle to estimate the altered fitness of the organism. For this study, we chose the lactose utilization system in E. coli. The system is extremely well characterized 20-22 , and hence amenable to accurate mathematical modelling. Further, many models describing the system dynamics already exist 18,19,22. Briefly, the lac operon system comprises of three genes, which are required for uptake and breakdown of lactose into simpler sugars (Fig. 1). These genes encode for a transporter LacY, a metabolic enzyme, LacZ, which metabolizes lactose into glucose and galactose, and a protein acetyltransferase LacA, which is believed to be involved in sugar metabolism via an unknown mechanism 23,24. The expression of lac operon is regulated by a repressor protein, LacI 23-27. In the absence of lactose, LacI binds the lac operon operator site and prevents transcription from the promoter. However, in presence of lactose, LacI preferentially binds a lactose molecule and thereafter is no longer able to bind the operator site of the lac operon, thus relieving the repression of the promoter. This makes transcription from the lac promoter conditional upon the presence of lactose in the environment 19,20,22,28-30. In this study, we simulate the system in a defined environment with fixed lactose concentration. We compute fitness in terms of a simple cost-benefit framework using the steady state values of the system. Using this framework, in addition to investigating the DFE associated with beneficial and deleterious mutations in the lac system, we seek to answer two specific questions. (1) How does the distribution of fitness effects change, with respect to the precise location on the fitness landscape? (2) How does this distribution vary between parameter sets associated with the network which correspond to the same fitness? To answer these questions, we choose parameter sets which correspond to low, medium and high fitness (with respect to global peak on the landscape) and introduce random mutations in the given parameter set, and note the fitness effect to build a frequency distribution associated with the parameter set. We also investigate the nature of epistatic effects between beneficial mutations using our model framework. Methods Model description. Lactose utilization in E. coli is enabled by the lac operon, which contains genes which encode for the sugar transporter LacY, the metabolic enzyme LacZ, and a protein LacA, which contributes towards lactose utilization via a yet to be characterized mechanism 31-33. The expression from the lac promoter is controlled by the repressor protein LacI. In absence of lactose, LacI binds to the lac promoter and prevents transcription. However, when lactose is present, LacI preferentially binds the lactose molecule. The lactose-LacI complex can no longer bind the operator site of lac operon, thus relieving transcriptional repression, and resulting
Frontiers in Cellular and Infection Microbiology
The food-borne pathogen Salmonella typhimurium is a common cause of infections and diseases in a ... more The food-borne pathogen Salmonella typhimurium is a common cause of infections and diseases in a wide range of hosts. One of the major virulence factors associated to the infection process is flagella, which helps the bacterium swim to its preferred site of infection inside the host, the M-cells (Microfold cells) lining the lumen of the small intestine. The expression of flagellar genes is controlled by an intricate regulatory network. In this work, we investigate two aspects of flagella regulation and assembly: (a) distribution of the number of flagella in an isogenic population of bacteria and (b) dynamics of gene expression post cell division. More precisely, in a population of bacteria, we note a normal distribution of number of flagella assembled per cell. How is this distribution controlled, and what are the key regulators in the network which help the cell achieve this? In the second question, we explore the role of protein secretion in dictating gene expression dynamics post cell-division (when the number of hook basal bodies on the cell surface is reduced by a factor of two). We develop a mathematical model and perform stochastic simulations to address these questions. Simulations of the model predict that two accessory regulators of flagella gene expression, FliZ and FliT, have significant roles in maintaining population level distribution of flagella. In addition, FliT and FlgM were predicted to control the level and temporal order of flagellar gene expression when the cell adapts to post cell division consequences. Further, the model predicts that, the FliZ and FliT dependent feedback loops function under certain thresholds, alterations in which can substantially affect kinetics of flagellar genes. Thus, based on our results we propose that, the proteins FlgM, FliZ, and FliT, thought to have accessory roles in regulation of flagella, likely play a critical role controlling gene expression during cell division, and frequency distribution of flagella.
Archives of Microbiology
Microbes have proved useful to us in many different ways. To utilize microbes, we have mostly foc... more Microbes have proved useful to us in many different ways. To utilize microbes, we have mostly focused on maximizing growth, to improve yield of chemicals derived from the microbes. However, to truly tap into their potential, we should also aim to understand microbial physiology. We present a historical perspective of the developments in the field of Microbial Biotechnology, focusing on how the growth-modelling approaches have changed. Starting from simple empirical growth models, we have evolved towards mechanistic and phenomenological models which use molecular and physiological details to drastically improve prediction power of these models. Lastly, we explore the as of yet unsolved questions in microbial physiology, and discuss how the ability to monitor microbial growth at single cell resolution using the lab-on-a-chip technologies is uncovering previously unobservable causal principles underlying microbial growth.
Frontiers in Ecology and Evolution
One of the central goals of ecology is to explain and predict coexistence of species. In this con... more One of the central goals of ecology is to explain and predict coexistence of species. In this context, microbial communities provide a model system where community structure can be studied in environmental niches and in laboratory conditions. A community of microbial population is stabilized by interactions between participating species. However, the nature of these stabilizing interactions has remained largely unknown. Theory and experiments have suggested that communities are stabilized by antagonistic interactions between member species, and destabilized by synergistic interactions. However, experiments have also revealed that a large fraction of all the interactions between species in a community are synergistic in nature. To understand the relative significance of the two types of interactions (synergistic vs. antagonistic) between species, we perform simulations of microbial communities with a small number of participating species using two frameworks—a replicator equation and...
Power flow analysis stands out as the foundation of power system preliminary research as well as ... more Power flow analysis stands out as the foundation of power system preliminary research as well as design. They are really essential for planning, operation, economic scheduling and interchange of power between utilities. The primary facts concerning power flow analysis are to identify the magnitude and phase angle of the voltage at every single bus and the real and reactive power flowing in each transmission system lines. The load flow study in a power system comprises a study of extremely important significance. The analysis uncovers the electrical performance and power flows (real and reactive) for stipulated circumstances whenever the system is functioning under the consistent state. This paper gives an overview of various techniques useful for load flow study under distinctive stipulated conditions.
Figure S1. The likelihood of reaching global optima increases from zero to one around critical va... more Figure S1. The likelihood of reaching global optima increases from zero to one around critical value of K when the benefit is higher than the cost. In this simulation the parameter (A) a is increased by a factor of 10; (B) parameter associated with cost per protein molecules (Îą) is increased by a factor of 10; (C) the parameter associated the sensitivity of the benefit function (b) is increased by a factor of 10; and (D) the parameter associated the sensitivity of the benefit function (b) is decreased by a factor of 10. Table S1. Parameter range of all 6 parameters (k, kr, kd, b, km, bas) used in the simulations. (DOCX 503 kb)
Frontiers in Microbiology
Environmental cues in an ecological niche are often temporal in nature. For instance, in temperat... more Environmental cues in an ecological niche are often temporal in nature. For instance, in temperate climates, temperature is higher in daytime compared to during night. In response to these temporal cues, bacteria have been known to exhibit anticipatory regulation, whereby triggering response to a yet to appear cue. Such an anticipatory response in known to enhance Darwinian fitness, and hence, is likely an important feature of regulatory networks in microorganisms. However, the conditions under which an anticipatory response evolves as an adaptive response are not known. In this work, we develop a quantitative model to study response of a population to two temporal environmental cues, and predict variables which are likely important for evolution of anticipatory regulatory response. We follow this with experimental evolution of Escherichia coli in alternating environments of rhamnose and paraquat for ∼850 generations. We demonstrate that growth in this cyclical environment leads to ...
Adaptive diversification of an isogenic population, and its molecular basis has been a subject of... more Adaptive diversification of an isogenic population, and its molecular basis has been a subject of a number of studies in the last few years. Microbial populations offer a relatively convenient model system to study this question. In this context, an isogenic population of bacteria (E. coli, B. subtilis, and Pseudomonas) has been shown to lead to genetic diversification in the population, when propagated for a number of generations. This diversification is known to occur when the individuals in the population have access to two or more resources/environments, which are separated either temporally or spatially. Here, we report adaptive diversification in an isogenic population of yeast, S. cerevisiae, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good, enzyme α-galactosidase, leading to hydrolysis of melibiose into two distinct resources, glucose and galactose. The diversification is driven by a mutations at ...
Mutations provide the raw material for natural selection to act. Therefore, understanding the var... more Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments performed with organisms such asDrosophilahave an effective population size of one. However, in MA experiments with bacteria and yeast, a single founder is allowed to grow to a size of a colony (~108). The effective population size in these experiments is of the order of 10. In this scenario, while it is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth and therefore, the MA experiment; this effect has not been tested explicitly. In this work, we simulate colony growth and perform an MA experiment, and demonstrate...
mSystems
Cooperative behaviors are highly prevalent in the wild, but their evolution is not understood. Me... more Cooperative behaviors are highly prevalent in the wild, but their evolution is not understood. Metabolic flux models can demonstrate the viability of metabolic exchange as cooperative interactions, but steady-state growth models cannot explain why cooperators grow faster.
Frontiers in Genetics
Heterogeneity among isogenic cells/individuals has been known for at least 150 years. Even Mendel... more Heterogeneity among isogenic cells/individuals has been known for at least 150 years. Even Mendel, working on pea plants, realized that not all tall plants were identical. However, Mendel was more interested in the discontinuous variation between genetically distinct individuals. The concept of environment dictating distinct phenotypes among isogenic individuals has since been shown to impact the evolution of populations in numerous examples at different scales of life. In this review, we discuss how phenotypic heterogeneity and its evolutionary implications exist at all levels of life, from viruses to mammals. In particular, we discuss how a particular disease condition (cancer) is impacted by heterogeneity among isogenic cells, and propose a potential role that phenotypic heterogeneity might play toward the onset of the disease.
Environmental cues in an ecological niche are temporal. In response to these temporal cues, bacte... more Environmental cues in an ecological niche are temporal. In response to these temporal cues, bacteria have been known to exhibit learning or conditioning, whereby they trigger response to a yet to appear cue, anticipating its actual arrival in the near future. Such an anticipatory response in known to enhance Darwinian fitness, and hence, is likely an important feature in the regulatory networks in microorganisms. However, the conditions under which an anticipatory response optimizes cellular fitness are not known. Nor has evolution of anticipatory regulation in laboratory conditions been experimentally demonstrated. In this work, we develop a quantitative model to study response of a population to two temporal environmental cues, and present the key variables in cellular physiology associated with response to the cues whose modulation is likely to lead to evolution of anticipatory regulatory response. We predict experimental conditions, which are likely to lead to demonstration of r...
The question of chance vs. determinism in dictating evolutionary trajectories has been a broad qu... more The question of chance vs. determinism in dictating evolutionary trajectories has been a broad question of interest in the last few decades. This question has not been addressed in the context of reverse evolution. By reverse evolution, we mean a scenario where selection is reversed. In this work, we use evolution of multicellularity in S. cerevisiae as a model to answer this question. When selected for fast-settling variants, multicellularity rapidly evolves in the organism. On reversing selection, unicellularity evolves from the multicellular clusters. However, the dynamic trajectories of the two processes are completely different. The molecular determinants dictating the two adaptive processes are also distinct from each other. In this context, evolution is not reversed dynamically or at a molecular level. The phenotypic reversal, however, is driven by epistatic interactions in the genome. How epistatic interactions evolve in a genome and shape evolutionary trajectories remains l...
Journal of the Indian Institute of Science
How Did It All Start Following Pasteur's discovery that yeast proliferates by fermenting glucose ... more How Did It All Start Following Pasteur's discovery that yeast proliferates by fermenting glucose to ethanol 1, 2 , Dienert observed that yeast exposed to glucose and galactose simultaneously, consumes glucose first and only when all the glucose in the media is exhausted, switches over to galactose 3. This phenomenon, rediscovered by Karstrome in bacteria 4 , gave birth to the concept of enzyme adaptation, where presence of the substrate drives the pre-existing equilibrium between inactive and active forms towards the active form 5. Monod,
Journal of the Indian Institute of Science
Introduction: Coordinated Behavior of Bacterial Populations Bacteria, when thought of with regard... more Introduction: Coordinated Behavior of Bacterial Populations Bacteria, when thought of with regards to their physiology and life cycle, are often viewed as single cells which make lifestyle decisions independent of their biological neighborhood. The physiological decisions made by this single cell are thought of as being driven solely towards the aim of increasing fitness of that particular individual bacterium. Therefore, bacteria were considered to live asocially with the sole of focus of maximizing chances of proliferation in a given environment. However, numerous ecological isolates reveal that bacteria rarely reside as a single species 1-4. Moreover, multiple species coexist and members from each are often interacting with each other. The most well studied niches in this context are intestines of mammals, biofilms on abiotic surfaces, or bacterial communities residing in soil. A study of physiology of bacteria residing in these niches suggests that bacteria residing here cooperate with each other, and this cooperation ensures maximization of fitness of the collective
Letters in Applied Microbiology
Bacteria frequently encounter multiple sugars in their natural surroundings. While the dynamics o... more Bacteria frequently encounter multiple sugars in their natural surroundings. While the dynamics of utilization of glucose‐containing sugar mixtures have been well investigated, there are few reports addressing regulation of utilization of glucose‐free mixtures particularly pentoses. These sugars comprise a considerable fraction in hemicellulose which can be converted by suitable biocatalysts to biofuels and other value‐added products. Hence, understanding of transcriptional cross‐regulation among different pentose sugar utilization systems is essential for successful development of industrial strains. In this work, we study mixed‐sugar utilization with respect to three secondary carbon sources — arabinose, xylose and rhamnose at single‐cell resolution in Escherichia coli. Our results reveal that hierarchical utilization among these systems is not strict but rather can be eliminated or reversed by altering the relative ratios of the preferred and nonpreferred sugars. Since transcriptional cross‐regulation among pentose sugar systems operates through competitive binding of noncognate sugar‐regulator complex, altering sugar concentrations is thought to eliminate nonspecific binding by affecting concentration of the regulator — sugar complexes.
The Canadian Journal of Chemical Engineering
Journal of Evolutionary Biology
Cellular energetics is thought to have played a key role in dictating all major evolutionary tran... more Cellular energetics is thought to have played a key role in dictating all major evolutionary transitions in the history of life on Earth. However, how exactly cellular energetics and metabolism come together to shape evolutionary paths is not well understood. In particular, when an organism is evolved in different energy environments, what are the phenomenological differences in the chosen evolutionary trajectories, is a question that is not well understood. In this context, starting from an Escherichia coli K‐12 strain, we evolve the bacterium in five different carbon environments—glucose, arabinose, xylose, rhamnose and a mixture of these four sugars (in a predefined ratio) for approximately 2,000 generations. At the end of the adaptation period, we quantify and compare the growth dynamics of the strains in a variety of environments. The evolved strains show no specialized adaptation towards growth in the carbon medium in which they were evolved. Rather, in all environments, the evolved strains exhibited a reduced lag phase and an increased growth rate. Sequencing results reveal that these dynamical properties are not introduced via mutations in the precise loci associated with utilization of the sugar in which the bacterium evolved. These phenotypic changes are rather likely introduced via mutations elsewhere on the genome. Data from our experiments indicate that evolution in a defined environment does not alter hierarchy in mixed‐sugar utilization in bacteria.
Starting from a parentalE. coliK-12 MG1655 strain, we evolve cells in five different carbon envir... more Starting from a parentalE. coliK-12 MG1655 strain, we evolve cells in five different carbon environments-glucose, arabinose, xylose, rhamnose, and a mixture of these four sugars (in a predefined ratio) for approximately 2,000 generations. At the end of the adaptation period, we quantify and compare growth dynamics of the strains in a variety of environments. The evolved strains show no specialized adaptation towards growth in the carbon medium in which they were evolved. Rather, in all environments, the evolved strains exhibited a reduced lag phase and an increased growth rate. Sequencing results reveal that these dynamical properties are not introduced via mutations in the precise loci associated with utilization of the sugar in which the bacterium was evolved in. These phenotypic changes are rather likely introduced via mutationselsewhere onthe genome. Sugar systems are known to exhibit hierarchy in utilization. Evolution in a defined environment, in our experimental framework, do...
Plasmodium parasite, a representative member of phylum Apicomplexa is a causative agent of malari... more Plasmodium parasite, a representative member of phylum Apicomplexa is a causative agent of malaria in human as well as other animals. To infect host cells, Plasmodium first finds receptors on the host cell surface, then binds specifically, and finally penetrates host cell membrane to acquire the host cellular resources. The motility for moving on the cell surface is equipped by the precise and tight control of actin treadmill. Several regulators are required to achieve precision and robustness in the control of actin treadmill. However, the mechanistic detail of the treadmill regulatory network and the cross-talk among regulators are not well understood. We developed a stochastic model of treadmill regulation and explored the dynamics of filament growth, nucleation time, and elongation time. Our study mainly highlighted on how and what helps cells to maintain an average size of the actin filaments within a species. This is particularly important, since, excessive growth of filament ...
Scientific Reports
demonstrated the first approach to estimate DFE, using Gillespie's mutational model, which uses E... more demonstrated the first approach to estimate DFE, using Gillespie's mutational model, which uses Extreme Value Theory to estimate that, statistically, beneficial mutations should be exponentially distributed 13. Satisfactory agreement with these predictions was found in a study where the authors study mutational effects in viruses 14. Subsequent approaches use statistical analysis applied on drosophila population data and human amino acid mutations (or SNPs), to estimate DFE of deleterious mutations 15-17. Approaches using population data assume that the present population is fitter with beneficial mutations enhanced in frequency, and thus, older variations must be lower in fitness. Minor variants that are declining in frequency are considered deleterious. The above approaches, either assume an abstract mutational model, or use existing dynamic population level data to estimate fitness effect sizes of mutations (Amino Acid variants or SNPs) in the populations. These help provide a general picture, but cannot capture the specific dynamics of a real biological system. These limitations motivated us to ask if it would be possible to obtain a specific fitness landscape and DFE of a biological system, derived from the mathematical model defined to functionally characterize the system. Such mathematical models of biological systems when tuned with experimentally derived parameter sets, have been extremely successful in describing the behaviour and dynamical properties of a number of systems 18,19. If these models truly capture the system's mechanistic dynamics, it is expected that it should also be able to predict the change in the system dynamics upon change in the system parameters by way of mutations, and hence give us a handle to estimate the altered fitness of the organism. For this study, we chose the lactose utilization system in E. coli. The system is extremely well characterized 20-22 , and hence amenable to accurate mathematical modelling. Further, many models describing the system dynamics already exist 18,19,22. Briefly, the lac operon system comprises of three genes, which are required for uptake and breakdown of lactose into simpler sugars (Fig. 1). These genes encode for a transporter LacY, a metabolic enzyme, LacZ, which metabolizes lactose into glucose and galactose, and a protein acetyltransferase LacA, which is believed to be involved in sugar metabolism via an unknown mechanism 23,24. The expression of lac operon is regulated by a repressor protein, LacI 23-27. In the absence of lactose, LacI binds the lac operon operator site and prevents transcription from the promoter. However, in presence of lactose, LacI preferentially binds a lactose molecule and thereafter is no longer able to bind the operator site of the lac operon, thus relieving the repression of the promoter. This makes transcription from the lac promoter conditional upon the presence of lactose in the environment 19,20,22,28-30. In this study, we simulate the system in a defined environment with fixed lactose concentration. We compute fitness in terms of a simple cost-benefit framework using the steady state values of the system. Using this framework, in addition to investigating the DFE associated with beneficial and deleterious mutations in the lac system, we seek to answer two specific questions. (1) How does the distribution of fitness effects change, with respect to the precise location on the fitness landscape? (2) How does this distribution vary between parameter sets associated with the network which correspond to the same fitness? To answer these questions, we choose parameter sets which correspond to low, medium and high fitness (with respect to global peak on the landscape) and introduce random mutations in the given parameter set, and note the fitness effect to build a frequency distribution associated with the parameter set. We also investigate the nature of epistatic effects between beneficial mutations using our model framework. Methods Model description. Lactose utilization in E. coli is enabled by the lac operon, which contains genes which encode for the sugar transporter LacY, the metabolic enzyme LacZ, and a protein LacA, which contributes towards lactose utilization via a yet to be characterized mechanism 31-33. The expression from the lac promoter is controlled by the repressor protein LacI. In absence of lactose, LacI binds to the lac promoter and prevents transcription. However, when lactose is present, LacI preferentially binds the lactose molecule. The lactose-LacI complex can no longer bind the operator site of lac operon, thus relieving transcriptional repression, and resulting
Frontiers in Cellular and Infection Microbiology
The food-borne pathogen Salmonella typhimurium is a common cause of infections and diseases in a ... more The food-borne pathogen Salmonella typhimurium is a common cause of infections and diseases in a wide range of hosts. One of the major virulence factors associated to the infection process is flagella, which helps the bacterium swim to its preferred site of infection inside the host, the M-cells (Microfold cells) lining the lumen of the small intestine. The expression of flagellar genes is controlled by an intricate regulatory network. In this work, we investigate two aspects of flagella regulation and assembly: (a) distribution of the number of flagella in an isogenic population of bacteria and (b) dynamics of gene expression post cell division. More precisely, in a population of bacteria, we note a normal distribution of number of flagella assembled per cell. How is this distribution controlled, and what are the key regulators in the network which help the cell achieve this? In the second question, we explore the role of protein secretion in dictating gene expression dynamics post cell-division (when the number of hook basal bodies on the cell surface is reduced by a factor of two). We develop a mathematical model and perform stochastic simulations to address these questions. Simulations of the model predict that two accessory regulators of flagella gene expression, FliZ and FliT, have significant roles in maintaining population level distribution of flagella. In addition, FliT and FlgM were predicted to control the level and temporal order of flagellar gene expression when the cell adapts to post cell division consequences. Further, the model predicts that, the FliZ and FliT dependent feedback loops function under certain thresholds, alterations in which can substantially affect kinetics of flagellar genes. Thus, based on our results we propose that, the proteins FlgM, FliZ, and FliT, thought to have accessory roles in regulation of flagella, likely play a critical role controlling gene expression during cell division, and frequency distribution of flagella.
Archives of Microbiology
Microbes have proved useful to us in many different ways. To utilize microbes, we have mostly foc... more Microbes have proved useful to us in many different ways. To utilize microbes, we have mostly focused on maximizing growth, to improve yield of chemicals derived from the microbes. However, to truly tap into their potential, we should also aim to understand microbial physiology. We present a historical perspective of the developments in the field of Microbial Biotechnology, focusing on how the growth-modelling approaches have changed. Starting from simple empirical growth models, we have evolved towards mechanistic and phenomenological models which use molecular and physiological details to drastically improve prediction power of these models. Lastly, we explore the as of yet unsolved questions in microbial physiology, and discuss how the ability to monitor microbial growth at single cell resolution using the lab-on-a-chip technologies is uncovering previously unobservable causal principles underlying microbial growth.