Modeling delayed processes in biological systems

Delayed processes are ubiquitous in biological systems and are often characterized by delay differential equations (DDEs) and their extension to include stochastic effects. DDEs do not explicitly incorporate intermediate states associated with a delayed process but instead use an estimated average delay time. In an effort to examine the validity of this approach, we study systems with significant delays by explicitly incorporating intermediate steps. We show by that such explicit models often yield significantly different equilibrium distributions and transition times as compared to DDEs with deterministic delay values. Additionally, different explicit models with qualitatively different dynamics can give rise to the same DDEs revealing important ambiguities. We also show that DDE-based predictions of oscillatory behavior may fail for the corresponding explicit model

Weed genomics : yielding insights into the genetics of weedy traits for crop improvement

Weeds cause tremendous economic and ecological damage worldwide. The number of genomes established for weed species has sharply increased during the recent decade, with some 26 weed species having been sequenced and de novo genomes assembled. These genomes range from 270 Mb (Barbarea vulgaris) to almost 4.4 Gb (Aegilops tauschii). Importantly, chromosome-level assemblies are now available for 17 of these 26 species, and genomic investigations on weed populations have been conducted in at least 12 species. The resulting genomic data have greatly facilitated studies of weed management and biology, especially origin and evolution. Available weed genomes have indeed revealed valuable weed-derived genetic materials for crop improvement. In this review, we summarize the recent progress made in weed genomics and provide a perspective for further exploitation in this emerging field

RACIPE: a computational tool for modeling gene regulatory circuits using randomization.

BACKGROUND: One of the major challenges in traditional mathematical modeling of gene regulatory circuits is the insufficient knowledge of kinetic parameters. These parameters are often inferred from existing experimental data and/or educated guesses, which can be time-consuming and error-prone, especially for large networks. RESULTS: We present a user-friendly computational tool for the community to use our newly developed method named random circuit perturbation (RACIPE), to explore the robust dynamical features of gene regulatory circuits without the requirement of detailed kinetic parameters. Taking the network topology as the only input, RACIPE generates an ensemble of circuit models with distinct randomized parameters and uniquely identifies robust dynamical properties by statistical analysis. Here, we discuss the implementation of the software and the statistical analysis methods of RACIPE-generated data to identify robust gene expression patterns and the functions of genes and regulatory links. Finally, we apply the tool on coupled toggle-switch circuits and a published circuit of B-lymphopoiesis. CONCLUSIONS: We expect our new computational tool to contribute to a more comprehensive and unbiased understanding of mechanisms underlying gene regulatory networks. RACIPE is a free open source software distributed under (Apache 2.0) license and can be downloaded from GitHub ( https://github.com/simonhb1990/RACIPE-1.0 )

Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by random circuit perturbation.

Stem cells can precisely and robustly undergo cellular differentiation and lineage commitment, referred to as stemness. However, how the gene network underlying stemness regulation reliably specifies cell fates is not well understood. To address this question, we applied a recently developed computational method, random circuit perturbation (RACIPE), to a nine-component gene regulatory network (GRN) governing stemness, from which we identified robust gene states. Among them, four out of the five most probable gene states exhibit gene expression patterns observed in single mouse embryonic cells at 32-cell and 64-cell stages. These gene states can be robustly predicted by the stemness GRN but not by randomized versions of the stemness GRN. Strikingly, we found a hierarchical structure of the GRN with the Oct4/Cdx2 motif functioning as the first decision-making module followed by Gata6/Nanog. We propose that stem cell populations, instead of being viewed as all having a specific cellular state, can be regarded as a heterogeneous mixture including cells in various states. Upon perturbations by external signals, stem cells lose the capacity to access certain cellular states, thereby becoming differentiated. The new gene states and key parameters regulating transitions among gene states proposed by RACIPE can be used to guide experimental strategies to better understand differentiation and design reprogramming. The findings demonstrate that the functions of the stemness GRN is mainly determined by its well-evolved network topology rather than by detailed kinetic parameters

Revisiting the Growth of Black Phosphorus in Sn-I Assisted Reactions

Black phosphorus, an emerging layered material, exhibits promising applications in diverse fields, ranging from electronics to optics. However, controlled synthesis of black phosphorus, particularly its few-layered counterparts, is still challenging, which should be due to the unclear growth mechanism of black phosphorus. Here, taking the most commonly used Sn-I assisted synthesis of black phosphorus as an example, we propose a growth mechanism of black phosphorus crystals by monitoring the reactions and analyzing the as-synthesized products. In the proposed mechanism, Sn24P19.3I8 is the active site for the growth of black phosphorus, and the black phosphorus crystals are formed with the assistance of SnI2, following a polymerization-like process. In addition, we suggest that all Sn-I assisted synthesis of black phosphorus should share the same reaction mechanism despite the differences among Sn-I containing additives. Our results shown here should shed light on the controlled synthesis of black phosphorus and facilitate further applications of black phosphorus

Distinguishing mechanisms underlying EMT tristability

Abstract Background The Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models – ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done. Results Here, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E→E/M→M, the different responses of SNAIL and ZEB1 to exogenous TGF-β and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2. Conclusions These experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes

The gut microbiome in atherosclerotic cardiovascular disease

The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease

Genome-wide selection footprints and deleterious variations in young Asian allotetraploid rapeseed

Brassica napus (AACC, 2n=38) is an important oilseed crop grown worldwide. However, little is known about the population evolution of this species, the genomic difference between its major genetic groups, such as European and Asian rapeseed, and the impacts of historical large-scale introgression events on this young tetraploid. In this study, we reported the de novo assembly of the genome sequences of an Asian rapeseed (B. napus), Ningyou 7 and its four progenitors and compared these genomes with other available genomic data from diverse European and Asian cultivars. Our results showed that Asian rapeseed originally derived from European rapeseed but subsequently significantly diverged, with rapid genome differentiation after hybridization and intensive local selective breeding. The first historical introgression of B. rapa dramatically broadened the allelic pool but decreased the deleterious variations of Asian rapeseed. The second historical introgression of the double-low traits of European rapeseed (canola) has reshaped Asian rapeseed into two groups (double-low and double-high), accompanied by an increase in genetic load in the double-low group. This study demonstrates distinctive genomic footprints and deleterious SNP (Single Nucleotide Polymorphism) variants for local adaptation by recent intra- and interspecies introgression events and provides novel insights for understanding the rapid genome evolution of a young allopolyploid cro