Generalized Michaelis-Menten rate law with time-varying molecular concentrations.

The Michaelis-Menten (MM) rate law has been the dominant paradigm of modeling biochemical rate processes for over a century with applications in biochemistry, biophysics, cell biology, systems biology, and chemical engineering. The MM rate law and its remedied form stand on the assumption that the concentration of the complex of interacting molecules, at each moment, approaches an equilibrium (quasi-steady state) much faster than the molecular concentrations change. Yet, this assumption is not always justified. Here, we relax this quasi-steady state requirement and propose the generalized MM rate law for the interactions of molecules with active concentration changes over time. Our approach for time-varying molecular concentrations, termed the effective time-delay scheme (ETS), is based on rigorously estimated time-delay effects in molecular complex formation. With particularly marked improvements in protein-protein and protein-DNA interaction modeling, the ETS provides an analytical framework to interpret and predict rich transient or rhythmic dynamics (such as autogenously-regulated cellular adaptation and circadian protein turnover), which goes beyond the quasi-steady state assumption.

Kernel Architecture of the Genetic Circuitry of the Arabidopsis Circadian System.

A wide range of organisms features molecular machines, circadian clocks, which generate endogenous oscillations with ~24 h periodicity and thereby synchronize biological processes to diurnal environmental fluctuations. Recently, it has become clear that plants harbor more complex gene regulatory circuits within the core circadian clocks than other organisms, inspiring a fundamental question: are all these regulatory interactions between clock genes equally crucial for the establishment and maintenance of circadian rhythms? Our mechanistic simulation for Arabidopsis thaliana demonstrates that at least half of the total regulatory interactions must be present to express the circadian molecular profiles observed in wild-type plants. A set of those essential interactions is called herein a kernel of the circadian system. The kernel structure unbiasedly reveals four interlocked negative feedback loops contributing to circadian rhythms, and three feedback loops among them drive the autonomous oscillation itself. Strikingly, the kernel structure, as well as the whole clock circuitry, is overwhelmingly composed of inhibitory, rather than activating, interactions between genes. We found that this tendency underlies plant circadian molecular profiles which often exhibit sharply-shaped, cuspidate waveforms. Through the generation of these cuspidate profiles, inhibitory interactions may facilitate the global coordination of temporally-distant clock events that are markedly peaked at very specific times of day. Our systematic approach resulting in experimentally-testable predictions provides insights into a design principle of biological clockwork, with implications for synthetic biology.

Fumarate-Mediated Persistence of Escherichia coli against Antibiotics.

Bacterial persisters are a small fraction of quiescent cells that survive in the presence of lethal concentrations of antibiotics. They can regrow to give rise to a new population that has the same vulnerability to the antibiotics as did the parental population. Although formation of bacterial persisters in the presence of various antibiotics has been documented, the molecular mechanisms by which these persisters tolerate the antibiotics are still controversial. We found that amplification of the fumarate reductase operon (FRD) inEscherichia coliled to a higher frequency of persister formation. The persister frequency ofE. coliwas increased when the cells contained elevated levels of intracellular fumarate. Genetic perturbations of the electron transport chain (ETC), a metabolite supplementation assay, and even the toxin-antitoxin-relatedhipA7mutation indicated that surplus fumarate markedly elevated theE. colipersister frequency. AnE. colistrain lacking succinate dehydrogenase (SDH), thereby showing a lower intracellular fumarate concentration, was killed ∼1,000-fold more effectively than the wild-type strain in the stationary phase. It appears thatSDHandFRDrepresent a paired system that gives rise to and maintainsE. colipersisters by producing and utilizing fumarate, respectively.

Halomonas sulfidaeris-dominated microbial community inhabits a 1.8 km-deep subsurface Cambrian Sandstone reservoir.

A low-diversity microbial community, dominated by the γ-proteobacterium Halomonas sulfidaeris, was detected in samples of warm saline formation porewater collected from the Cambrian Mt. Simon Sandstone in the Illinois Basin of the North American Midcontinent (1.8 km/5872 ft burial depth, 50°C, pH 8, 181 bars pressure). These highly porous and permeable quartz arenite sandstones are directly analogous to reservoirs around the world targeted for large-scale hydrocarbon extraction, as well as subsurface gas and carbon storage. A new downhole low-contamination subsurface sampling probe was used to collect in situ formation water samples for microbial environmental metagenomic analyses. Multiple lines of evidence suggest that this H. sulfidaeris-dominated subsurface microbial community is indigenous and not derived from drilling mud microbial contamination. Data to support this includes V1-V3 pyrosequencing of formation water and drilling mud, as well as comparison with previously published microbial analyses of drilling muds in other sites. Metabolic pathway reconstruction, constrained by the geology, geochemistry and present-day environmental conditions of the Mt. Simon Sandstone, implies that H. sulfidaeris-dominated subsurface microbial community may utilize iron and nitrogen metabolisms and extensively recycle indigenous nutrients and substrates. The presence of aromatic compound metabolic pathways suggests this microbial community can readily adapt to and survive subsurface hydrocarbon migration.

Multi-study integration of brain cancer transcriptomes reveals organ-level molecular signatures.

We utilized abundant transcriptomic data for the primary classes of brain cancers to study the feasibility of separating all of these diseases simultaneously based on molecular data alone. These signatures were based on a new method reported herein--Identification of Structured Signatures and Classifiers (ISSAC)--that resulted in a brain cancer marker panel of 44 unique genes. Many of these genes have established relevance to the brain cancers examined herein, with others having known roles in cancer biology. Analyses on large-scale data from multiple sources must deal with significant challenges associated with heterogeneity between different published studies, for it was observed that the variation among individual studies often had a larger effect on the transcriptome than did phenotype differences, as is typical. For this reason, we restricted ourselves to studying only cases where we had at least two independent studies performed for each phenotype, and also reprocessed all the raw data from the studies using a unified pre-processing pipeline. We found that learning signatures across multiple datasets greatly enhanced reproducibility and accuracy in predictive performance on truly independent validation sets, even when keeping the size of the training set the same. This was most likely due to the meta-signature encompassing more of the heterogeneity across different sources and conditions, while amplifying signal from the repeated global characteristics of the phenotype. When molecular signatures of brain cancers were constructed from all currently available microarray data, 90% phenotype prediction accuracy, or the accuracy of identifying a particular brain cancer from the background of all phenotypes, was found. Looking forward, we discuss our approach in the context of the eventual development of organ-specific molecular signatures from peripheral fluids such as the blood.

Inactivation of phosphodiesterase-4B gene in rat nucleus accumbens shell by CRISPR/Cas9 or positive allosteric modulation of the protein affects the motivation to chronically self-administer nicotine.

Large scale human genome wide association studies (GWAS) have identified a growing pool of genes associated with cigarette smoking. One of the most prominent, phosphodiesterase-4B (PDE4B), has been associated with multiple smoking phenotypes. Although PDE4B modulates the half-life of neuronal cAMP, its precise role in smoking behaviors is unknown. To address this knowledge gap, we used a reverse translational approach. We inactivated PDE4B in bilateral medial nucleus accumbens shell (NAcs) neurons by injecting AAV containing a specific gRNA in female transgenic Cas9+ Long Evans rats. These rats then were given 23-h chronic access to nicotine intravenous self-administration (IVSA) under a schedule of increasing fixed ratios (FR). With the increased effort required at FR7, nicotine SA (i.e. active presses and drug infusions) declined significantly in controls, whereas it was maintained in the mutagenized group. A progressive ratio (PR) study also showed significantly greater cumulative nicotine infusions in the PDE4B-edited group. Hence, we hypothesized that enhanced PDE4B protein activity would reduce nicotine IVSA. A positive allosteric modulator, 2-(3-(4-chloro-3-fluorophenyl)-5-ethyl-1H-1,2,4-triazol-1-yl)-N-(3,5-dichlorobenzyl)acetamide (MR-L2), was microinfused into NAcs bilaterally at FR3 or FR5; in both cohorts, MR-L2 acutely reduced nicotine IVSA. In summary, these studies show that the activity of PDE4B regulates the capacity of NAcs to maintain nicotine IVSA in face of the cost of increasing work. This finding and the results of the PR study indicate that PDE4B affects the motivation to obtain nicotine. These reverse translational studies in rats provide insight into the motivational effects of NAcs PDE4B that advance our understanding of the smoking behaviors mapped in human GWAS.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats.

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

Inactivation of phosphodiesterase-4B gene in rat nucleus accumbens shell by CRISPR/Cas9 modulates the motivation to chronically self-administer nicotine.

Large scale human genome wide association studies (GWAS) have identified a growing pool of genes associated with cigarette smoking. One of the most prominent, phosphodiesterase-4B (PDE4B), has been associated with multiple smoking phenotypes. Although PDE4B modulates the half-life of neuronal cAMP, its precise role in smoking behaviors is unknown. To address this knowledge gap, we used a reverse translational approach. We inactivated PDE4B in bilateral medial nucleus accumbens shell (NAcs) neurons by injecting AAV containing a specific gRNA in female transgenic Cas9+ Long Evans rats. These rats then were given 23-hour chronic access to nicotine intravenous self-administration (IVSA) under a schedule of increasing fixed ratios (FR). With the increased effort required at FR7, nicotine SA (i.e. active presses and drug infusions) declined significantly in controls, whereas it was maintained in the mutagenized group. A progressive ratio (PR) study also showed significantly greater cumulative nicotine infusions in the mutant group. Hence, we hypothesized that enhanced PDE4B protein activity would reduce nicotine IVSA. A positive allosteric modulator,2-(3-(4-chloro-3-fluorophenyl)-5-ethyl-1H-1,2,4-triazol-1-yl)-N-(3,5-dichlorobenzyl)acetamide (MR-L2), was microinfused into NAcs bilaterally at FR3 or FR5; in both cohorts, MR-L2 acutely reduced nicotine IVSA. In summary, these studies show that the activity of PDE4B regulates the capacity of NAcs to maintain nicotine IVSA in face of the cost of increasing work. This finding and the results of the PR study indicate that PDE4B affects the motivation to obtain nicotine. These reverse translational studies in rats provide insight into the motivational effects of NAcs PDE4B that advance our understanding of the smoking behaviors mapped in human GWAS.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats.

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared to its predecessor. Gene annotations are now more complete, significantly improving the mapping precision of genomic, transcriptomic, and proteomics data sets. We jointly analyzed 163 short-read whole genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ~20.0 million sequence variations, of which 18.7 thousand are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

Genetic co-occurrence network across sequenced microbes.

The phenotype of any organism on earth is, in large part, the consequence of interplay between numerous gene products encoded in the genome, and such interplay between gene products affects the evolutionary fate of the genome itself through the resulting phenotype. In this regard, contemporary genomes can be used as molecular records that reveal associations of various genes working in their natural lifestyles. By analyzing thousands of orthologs across ∼600 bacterial species, we constructed a map of gene-gene co-occurrence across much of the sequenced biome. If genes preferentially co-occur in the same organisms, they were called herein correlogs; in the opposite case, called anti-correlogs. To quantify correlogy and anti-correlogy, we alleviated the contribution of indirect correlations between genes by adapting ideas developed for reverse engineering of transcriptional regulatory networks. Resultant correlogous associations are highly enriched for physically interacting proteins and for co-expressed transcripts, clearly differentiating a subgroup of functionally-obligatory protein interactions from conditional or transient interactions. Other biochemical and phylogenetic properties were also found to be reflected in correlogous and anti-correlogous relationships. Additionally, our study elucidates the global organization of the gene association map, in which various modules of correlogous genes are strikingly interconnected by anti-correlogous crosstalk between the modules. We then demonstrate the effectiveness of such associations along different domains of life and environmental microbial communities. These phylogenetic profiling approaches infer functional coupling of genes regardless of mechanistic details, and may be useful to guide exogenous gene import in synthetic biology.

Backward simulation for inferring hidden biomolecular kinetic profiles.

Our backward simulation (BS) is an approach to infer the dynamics of individual components in ordinary differential equation (ODE) models, given the information on relatively downstream components or their sums. Here, we demonstrate the use of BS to infer protein synthesis rates with a given profile of protein concentrations over time in a circadian system. This protocol can also be applied to a wide range of problems with undetermined dynamics at the upstream levels. For complete details on the use and execution of this protocol, please refer to Lim et al. (2021).

Cost-effective circadian mechanism: rhythmic degradation of circadian proteins spontaneously emerges without rhythmic post-translational regulation.

Circadian protein oscillations are maintained by the lifelong repetition of protein production and degradation in daily balance. It comes at the cost of ever-replayed, futile protein synthesis each day. This biosynthetic cost with a given oscillatory protein profile is relievable by a rhythmic, not constant, degradation rate that selectively peaks at the right time of day but remains low elsewhere, saving much of the gross protein loss and of the replenishing protein synthesis. Here, our mathematical modeling reveals that the rhythmic degradation rate of proteins with circadian production spontaneously emerges under steady and limited activity of proteolytic mediators and does not necessarily require rhythmic post-translational regulation of previous focus. Additional (yet steady) post-translational modifications in a proteolytic pathway can further facilitate the degradation's rhythmicity in favor of the biosynthetic cost saving. Our work is supported by animal and plant circadian data, offering a generic mechanism for potentially widespread, time-dependent protein turnover.

Whole genome sequencing of nearly isogenic WMI and WLI inbred rats identifies genes potentially involved in depression and stress reactivity.

The WMI and WLI inbred rats were generated from the stress-prone, and not yet fully inbred, Wistar Kyoto (WKY) strain. These were selected using bi-directional selection for immobility in the forced swim test and were then sib-mated for over 38 generations. Despite the low level of genetic diversity among WKY progenitors, the WMI substrain is significantly more vulnerable to stress relative to the counter-selected WLI strain. Here we quantify numbers and classes of genomic sequence variants distinguishing these substrains with the long term goal of uncovering functional and behavioral polymorphism that modulate sensitivity to stress and depression-like phenotypes. DNA from WLI and WMI was sequenced using Illumina xTen, IonTorrent, and 10X Chromium linked-read platforms to obtain a combined coverage of ~ 100X for each strain. We identified 4,296 high quality homozygous SNPs and indels between the WMI and WLI. We detected high impact variants in genes previously implicated in depression (e.g. Gnat2), depression-like behavior (e.g. Prlr, Nlrp1a), other psychiatric disease (e.g. Pou6f2, Kdm5a, Reep3, Wdfy3), and responses to psychological stressors (e.g. Pigr). High coverage sequencing data confirm that the two substrains are nearly coisogenic. Nonetheless, the small number of sequence variants contributes to numerous well characterized differences including depression-like behavior, stress reactivity, and addiction related phenotypes. These selected substrains are an ideal resource for forward and reverse genetic studies using a reduced complexity cross.

Macroscopic kinetic effect of cell-to-cell variation in biochemical reactions.

Genetically identical cells under the same environmental conditions can show strong variations in protein copy numbers due to inherently stochastic events in individual cells. We here develop a theoretical framework to address how variations in enzyme abundance affect the collective kinetics of metabolic reactions observed within a population of cells. Kinetic parameters measured at the cell population level are shown to be systematically deviated from those of single cells, even within populations of homogeneous parameters. Because of these considerations, Michaelis-Menten kinetics can even be inappropriate to apply at the population level. Our findings elucidate a novel origin of discrepancy between in vivo and in vitro kinetics, and offer potential utility for analysis of single-cell metabolomic data.

Large-scale metabolic interaction network of the mouse and human gut microbiota.

The role of our gut microbiota in health and disease is largely attributed to the collective metabolic activities of the inhabitant microbes. A system-level framework of the microbial community structure, mediated through metabolite transport, would provide important insights into the complex microbe-microbe and host-microbe chemical interactions. This framework, if adaptable to both mouse and human systems, would be useful for mechanistic interpretations of the vast amounts of experimental data from gut microbiomes in murine animal models, whether humanized or not. Here, we constructed a literature-curated, interspecies network of the mammalian gut microbiota for mouse and human hosts, called NJC19. This network is an extensive data resource, encompassing 838 microbial species (766 bacteria, 53 archaea, and 19 eukaryotes) and 6 host cell types, interacting through 8,224 small-molecule transport and macromolecule degradation events. Moreover, we compiled 912 negative associations between organisms and metabolic compounds that are not transportable or degradable by those organisms. Our network may facilitate experimental and computational endeavors for the mechanistic investigations of host-associated microbial communities.

Publisher Correction: Large-scale metabolic interaction network of the mouse and human gut microbiota.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Nutritionally recommended food for semi- to strict vegetarian diets based on large-scale nutrient composition data.

Diet design for vegetarian health is challenging due to the limited food repertoire of vegetarians. This challenge can be partially overcome by quantitative, data-driven approaches that utilise massive nutritional information collected for many different foods. Based on large-scale data of foods' nutrient compositions, the recent concept of nutritional fitness helps quantify a nutrient balance within each food with regard to satisfying daily nutritional requirements. Nutritional fitness offers prioritisation of recommended foods using the foods' occurrence in nutritionally adequate food combinations. Here, we systematically identify nutritionally recommendable foods for semi- to strict vegetarian diets through the computation of nutritional fitness. Along with commonly recommendable foods across different diets, our analysis reveals favourable foods specific to each diet, such as immature lima beans for a vegan diet as an amino acid and choline source, and mushrooms for ovo-lacto vegetarian and vegan diets as a vitamin D source. Furthermore, we find that selenium and other essential micronutrients can be subject to deficiency in plant-based diets, and suggest nutritionally-desirable dietary patterns. We extend our analysis to two hypothetical scenarios of highly personalised, plant-based methionine-restricted diets. Our nutrient-profiling approach may provide a useful guide for designing different types of personalised vegetarian diets.

Waveforms of molecular oscillations reveal circadian timekeeping mechanisms.

Circadian clocks play a pivotal role in orchestrating numerous physiological and developmental events. Waveform shapes of the oscillations of protein abundances can be informative about the underlying biochemical processes of circadian clocks. We derive a mathematical framework where waveforms do reveal hidden biochemical mechanisms of circadian timekeeping. We find that the cost of synthesizing proteins with particular waveforms can be substantially reduced by rhythmic protein half-lives over time, as supported by previous plant and mammalian data, as well as our own seedling experiment. We also find that previously enigmatic, cyclic expression of positive arm components within the mammalian and insect clocks allows both a broad range of peak time differences between protein waveforms and the symmetries of the waveforms about the peak times. Such various peak-time differences may facilitate tissue-specific or developmental stage-specific multicellular processes. Our waveform-guided approach can be extended to various biological oscillators, including cell-cycle and synthetic genetic oscillators.

Emergence of chaotic itinerancy in simple ecological systems.

Chaotic itinerancy is a universal dynamical concept that describes itinerant motion among many different ordered states through chaotic transition in dynamical systems. Unlike the expectation of the prevalence of chaotic itinerancy in high-dimensional systems, we identify chaotic itinerant behavior from a relatively simple ecological system, which consists only of two coupled consumer-resource pairs. The system exhibits chaotic bursting activity, in which the explosion and the shrinkage of the population alternate indefinitely, while the explosion of one pair co-occurs with the shrinkage of the other pair. We analyze successfully the bursting activity in the framework of chaotic itinerancy, and find that large duration times of bursts tend to cluster in time, allowing the effective burst prognosis. We also investigate the control schemes on the bursting activity, and demonstrate that invoking the competitive rise of the consumer in one pair can even elongate the burst of the other pair rather than shorten it.

Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis.

A system-level framework of complex microbe-microbe and host-microbe chemical cross-talk would help elucidate the role of our gut microbiota in health and disease. Here we report a literature-curated interspecies network of the human gut microbiota, called NJS16. This is an extensive data resource composed of ∼570 microbial species and 3 human cell types metabolically interacting through >4,400 small-molecule transport and macromolecule degradation events. Based on the contents of our network, we develop a mathematical approach to elucidate representative microbial and metabolic features of the gut microbial community in a given population, such as a disease cohort. Applying this strategy to microbiome data from type 2 diabetes patients reveals a context-specific infrastructure of the gut microbial ecosystem, core microbial entities with large metabolic influence, and frequently produced metabolic compounds that might indicate relevant community metabolic processes. Our network presents a foundation towards integrative investigations of community-scale microbial activities within the human gut.