Biology subjects

Loh, Y. L.

Publications and source records attributed to Loh, Y. L..

3 recordsLinked to original sources

bioRxiv2025

The differentiation of myeloid progenitors is effected by cascading waves of coordinated gene expression that remodel cellular physiology in a characteristic sequence

The differentiation of hematopoietic progenitors into specialized types requires the transmittal of information from a few external or internal regulators to the thousands of genes that produce a cell types characteristic phenotypes. While the main signaling pathways, transcription factors, and the genes eliciting the terminal phenotypes are known, how information flows from a few regulators to thousands of genes to change the state of the cell remains to be fleshed out. To profile this information transfer process, we sampled the differentiation of the PUER myeloid cell line into macrophages and neutrophils at 29 time points over seven days. There is extensive transient regulation; the number of transcripts modulated in time is twice the number differentially expressed between endpoints. Differentiation is marked by two sharp transitions, at [~] 8h and [~] 80h, when transcriptomic state changes suddenly. We utilized non-negative matrix factorization to identify behaviors, characteristic temporal patterns of gene expression, and to classify transcripts by behavior. Only 10 distinct behaviors are sufficient to recapitulate the expression of [~]36,000 transcripts with high fidelity. Gene expression in most of the behaviors occurs in pulses of varying initiation times and durations. This implies that information transfer during differentiation occurs in cascading waves of gene expression culminating in the permanent turning on of certain genes after [~] 80h. Each behavior is enriched in specific biological processes, so that physiological remodeling proceeds in a characteristic order--signal transduction, translation and mRNA processing, metabolism, and, ultimately, myeloid phenotypic processes. The sharp transition at 8h corresponds to the completion of transcriptional and translational remodeling and the initiation of metabolic remodeling; the one at 80h corresponds to the elicitation of myeloid phenotypes. Our analysis shows that differentiation relies upon a series of transient, rapid, and complex gene regulatory events and highlights the importance of profiling it at a high temporal resolution. Author summaryThe maturation of hematopoietic progenitor cells into differentiated cell types occurs over a period of about a week. This process requires the progenitors to respond to external signals by changing the expression of thousands of genes to elicit the required phenotypes. We profiled how information is transferred from a few upstream regulators to thousands of genes by measuring genome-wide gene expression at high temporal resolution during white-blood cell differentiation. We show that the information transfer occurs in cascading waves, some as short as 8 hours and others lasting for 3 days, in which thousands of genes change expression coordinately. The physiological processes remodeled in each successive wave follow a characteristic order, starting with signal transduction pathways, followed by translation and mRNA processing, then metabolism, and culminating in the production of innate immunity phenotypes. Maturation is also punctuated with two sharp transitions, when genome-wide expression changes suddenly, associated with the initiation of metabolic remodeling and the production of terminal phenotypes. Our analysis shows that a complete description of differentiation requires the characterization of transient changes and not just those observable at the endpoints.

developmental biology↗

bioRxiv2024

Detection of tomato brown rugose fruit virus in environmental residues: the importance of contextualizing test results

Tomato brown rugose fruit virus (ToBRFV) is regulated as a quarantine pest in many countries worldwide. To assess whether ToBRFV is present in cultivations, plants or seed lots, testing is required. The interpretation of test results, however, can be challenging. Real-time RT-PCR results, even though considered "positive", may not always signify plant infection or indicate the presence of infectious virus, but could be due to the presence of viral residues in the environment. Here, case studies from the Netherlands, Belgium, and the United Kingdom address questions regarding the detection of ToBRFV in various settings, and the infectiousness of ToBRFV positive samples. These exploratory analyses demonstrate widespread detection of ToBRFV in diverse samples and environments. ToBRFV was detected inside and around greenhouses with no prior history of ToBRFV infection, on different materials and surfaces including those that were untouched by individuals, plants, or objects. This suggested the dispersal of viral residues through aerosols. ToBRFV or its residues were more often detected in areas with nearby tomato production yet were also found in a wider environment extending beyond infected crops. Given that ToBRFV originating from environmental contamination may or may not be infectious, adds complexity to decision-making in response to positive test results. Contextual information, such as the origin of the sample and the likelihood of residues from prior cultivations and/or the broader environment, is important for interpreting test results. A nuanced approach is crucial to correctly interpret ToBRFV test results, necessitating further research to support risk assessment.

microbiology↗

bioRxiv2019

Classification-based Inference of Dynamical Models of Gene Regulatory Networks

Cell-fate decisions during development are controlled by densely interconnected gene regulatory networks (GRNs) consisting of many genes. Inferring and predictively modeling these GRNs is crucial for understanding development and other physiological processes. Gene circuits, coupled differential equations that represent gene product synthesis with a switch-like function, provide a biologically realistic framework for modeling the time evolution of gene expression. However, their use has been limited to smaller networks due to the computational expense of inferring model parameters from gene expression data using global non-linear optimization. Here we show that the switch-like nature of gene regulation can be exploited to break the gene circuit inference problem into two simpler optimization problems that are amenable to computationally efficient supervised learning techniques. We present FIGR (Fast Inference of Gene Regulation), a novel classification-based inference approach to determining gene circuit parameters. We demonstrate FIGRs effectiveness on synthetic data as well as experimental data from the gap gene system of Drosophila. FIGR is faster than global non-linear optimization by nearly three orders of magnitude and its computational complexity scales much better with GRN size. On a practical level, FIGR can accurately infer the biologically realistic gap gene network in under a minute on desktop-class hardware instead of requiring hours of parallel computing. We anticipate that FIGR would enable the inference of much larger biologically realistic GRNs than was possible before. FIGR Source code is freely available at http://github.com/mlekkha/FIGR.

systems biology↗