Biology subjects

Patel, E.

Publications and source records attributed to Patel, E..

4 recordsLinked to original sources

bioRxiv2024

Asynchronous mouse embryo polarization leads to heterogeneity in cell fate specification

The first lineage allocation in mouse and human embryos separates the inner cell mass (ICM) from the outer trophectoderm (TE). This symmetry breaking event is executed through polarization of cells at the 8-cell stage and subsequent asymmetric divisions, generating polar (TE) and apolar (ICM) cells. Here, we show that embryo polarization is unexpectedly asynchronous. Cells polarizing at the early and late 8-cell stage have distinct molecular and morphological properties that direct their following lineage specification, with early polarizing cells being biased towards producing the TE lineage. More recent studies have also implicated heterogeneities between cells prior to the 8-cell stage in the first lineage allocation: cells exhibiting reduced methyltransferase CARM1 activity at the 4-cell stage are predisposed towards the TE fate. Here, we demonstrate that reduced CARM1 activity and upregulation of its substrate BAF155 promote early polarization and TE specification. These findings provide a link between asymmetries at the 4-cell stage and polarization at the 8-cell stage, mechanisms of the first lineage allocation that had been considered separate.

developmental biology↗

bioRxiv2024

Microdroplet screening rapidly profiles a biocatalyst to enable its AI-assisted engineering

Engineering enzymes for increased efficiency is key to enabling sustainable, green biocatalytic production processes in the chemical and pharmaceutical industries. This challenge can be tackled from two angles: by directed evolution, based on labour-intensive experimental testing of enzyme variant libraries, or by computational methods, where data-dependent algorithms relating sequence and function are used to predict biocatalyst improvements. Here, we combine both approaches into a two-week, low-cost workflow, in which ultra-high throughput screening of a library of imine reductases (IREDs) in microfluidic devices provides not only selected hits, but also long-read sequence data linked to fitness scores of >17 thousand enzyme variants. We demonstrate the engineering of an IRED for chiral amine synthesis by mapping its local fitness landscape in one go, ready to be used for interpretation and extrapolation by protein engineers with the help of machine learning (ML). We calculate position-dependent mutability and combinability scores of mutations and comprehensively illuminate a complex interplay of mutations driven by synergistic, often positively epistatic effects. When interpreted by easy-to-use regression and tree-based ML algorithms designed for random whole-gene mutagenesis data, 3-fold improved hits initially obtained from experimental screening are extrapolated further to give another order of magnitude improvement (23-fold in kcat) after testing only a handful of designed mutants. Predictions succeed in >80% of cases. The catalytic features discovered in one IRED are shown to be portable and confer activity on IREDs with [~]50% homology. Our campaigns yield biocatalytically efficient IREDs and are paradigmatic for future enzyme engineering efforts that rely on large sequence-function maps, profiling how a biocatalyst responds to mutation. In the age of predictive biology, these maps will chart the way to improved function by exploiting the synergy of rapid experimental screening combined with ML evaluation and extrapolation.

synthetic biology↗

bioRxiv2024

Coordinated regulation by lncRNAs results in tight lncRNA-target couplings

The determination of long non-coding RNA (lncRNA) function is a major challenge in RNA biology with applications to basic, translational, and medical research [1-7]. Our efforts to improve the accuracy of lncRNA-target inference identified lncRNAs that coordinately regulate both the transcriptional and post-transcriptional processing of their targets. Namely, these lncRNAs may regulate the transcription of their target and chaperone the resulting message until its translation, leading to tightly coupled lncRNA and target abundance. Our analysis suggested that hundreds of cancer genes are coordinately and tightly regulated by lncRNAs and that this unexplored regulatory paradigm may propagate the effects of non-coding alterations to effectively dysregulate gene expression programs. As a proof-of-principle we studied the regulation of DICER1 [8, 9]--a cancer gene that controls microRNA biogenesis--by the lncRNA ZFAS1, showing that ZFAS1 activates DICER1 transcription and blocks its post-transcriptional repression to phenomimic and regulate DICER1 and its target microRNAs.

bioinformatics↗

bioRxiv2020

Dystrophic microglia are a disease associated microglia morphology in the human brain

Microglia activation--typically described in terms of hypertrophic appearance--is a well-established feature of aging. Recent studies have suggested that microglia dystrophy, not activation, may increase the propagation of progressive neurodegenerative diseases such as Alzheimers disease (AD). Yet, a clear understanding of cause and consequences of dystrophic microglia is lacking. Although frequently observed in diseased brains, the appearance of dystrophic microglia in the hippocampus of individuals free of cognitive impairment suggests that microglia may be undergoing senescence with age, leading to dystrophy. Therefore, we hypothesized that chronological age could be a significant contributor to the presence of dystrophic microglia. To investigate this relationship, we employed stereological counts of total microglia, hypertrophic, and dystrophic microglia across the decades of the human lifespan. The microglia counts were performed in the frontal cortex gray and white matter and the CA1 subregion of the hippocampus in individuals without known neurodegenerative disease. There was age-associated increase in the number of dystrophic microglia in the CA1 region and the frontal cortex gray matter related to age. However, the increase in dystrophic microglia was proportional to the age-related increase in the total number of microglia, suggesting that aging alone was not sufficient to explain the presence of dystrophic microglia. We next tested if dystrophic microglia could be a disease-associated microglia phenotype. Compared to controls without neuropathology, the number of dystrophic microglia was significantly greater in aged-matched cases with either AD, dementia with Lewy bodies, or LATE-NC. These results provide evidence that healthy aging is only associated with a modest increase in dystrophic microglia and suggest that dystrophic microglia may be a disease-associated microglia phenotype. Finally, we found strong evidence for iron homeostasis changes, with increases in ferritin light chain, in dystrophic microglia compared to ramified or hypertrophic microglia. Based on our findings, microglia dystrophy, and not hypertrophic microglia, are the disease-associated microglia morphology. Future work is required to understand the links between the increase in dystrophic microglia and neurodegenerative disorders.

neuroscience↗