PLoS Biology最新文献

Maintenance of somatic sex identity is essential for adult tissue function. In the Drosophila testis, adult somatic stem cells known as cyst stem cells (CySCs) require the transcription factor Chinmo to preserve male identity. Loss of Chinmo leads to reprogramming of CySCs into their ovarian counterparts through induction of the female-specific RNA-binding protein TransformerF (TraF), though the underlying mechanism has remained unclear. Here, we identify the pioneer transcription factor Zelda (Zld) as a critical mediator of this sex reversal. In wild-type CySCs, zld mRNA is repressed by microRNAs (miRs), but following Chinmo loss, these miRs are downregulated, allowing zld mRNA to be translated. Zld is necessary for feminization of chinmo-mutant CySCs, and ectopic expression of Zld in wild-type CySCs is sufficient to induce TraF and drive female reprogramming. Two Zld target genes, qkr58E-2 and Ecdysone receptor (EcR), are upregulated in chinmo-mutant CySCs and are normally female-biased in adult gonads. Qkr58E-2 facilitates TraF production, while EcR promotes female gene expression programs. Zld overexpression feminizes otherwise wild-type CySCs by upregulating EcR, which in turn downregulates the chinmo gene. Strikingly, overexpression of Zld also feminizes adult male adipose tissue by inducing TraF and downregulating Chinmo, indicating that Zld can override male identity in multiple adult XY tissues. Together, these findings uncover a post-transcriptional mechanism in which miRs-mediated repression of a pioneer factor safeguards male identity and prevents inappropriate activation of the female program in adult somatic cells.

Enteroendocrine cells (EECs) are rare sensory cells in the intestinal epithelium that coordinate digestive physiology by secreting a diverse repertoire of peptide hormones. These hormones are the main effectors of EEC function, and their characterization requires direct observation by mass spectrometry due to the specialized protein cleavage and posttranslational modifications that yield their mature forms. Based on the distinct subset of hormones they predominantly secrete, EECs can be categorized into subtypes. How each EEC subtype is specified, however, remains poorly understood. Here, we describe EEC subtype differentiation and hormone production in the zebrafish. Using single-cell RNA sequencing data, we identified EEC progenitors and six EEC subtypes in zebrafish and revealed that their expression profiles are consistent across larval and adult stages. Mass spectrometry analysis of isolated zebrafish EECs identified highly processed peptides derived from 19 of 23 hormone-coding genes expressed by EECs, including a previously undescribed zebrafish secretin ortholog. We assembled reporters for zebrafish EEC subtypes to test the lineage relationships between EEC subtypes and the EEC progenitor population, which expresses neurogenin 3 (neurog3). Despite its essential role in mammalian EEC differentiation, we found that selective cytotoxic ablation of neurog3+ cells in zebrafish only reduced a subset of EEC subtypes and loss of the neurog3 gene had no impact on EEC numbers. Finally, we discovered that selective ablation of ghrelin+ EECs reduced a different subset of EEC subtypes, together suggesting that neurog3+ and ghrelin+ cells serve as distinct precursors for separate EEC subtypes. We anticipate these observations and resources will facilitate future studies in the zebrafish to discern the developmental biology, physiology, and endocrinology of EEC subtypes.

2025 was marked by upheaval and uncertainty for many within the life science community. As we reflect on the year that has gone, we highlight some of the many research achievements that give us reasons to be thankful.

Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for the surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR and identify resistance determinants. However, bacterial populations are highly structured, and sampling is biased towards human disease isolates, violating ML assumptions of independence between samples. This is rarely considered in applications of ML to AMR. Here, we demonstrate the confounding effects of sample structure by analyzing over 24,000 whole genome sequences and AMR phenotypes from five diverse pathogens, using pathological training data where resistance is confounded with phylogeny. We show the resulting ML models perform poorly and that increasing the training sample size fails to rescue performance. A comprehensive analysis of 6,740 models identifies species- and drug-specific effects on model accuracy. These findings highlight the limitations of current ML approaches in the face of realistic sampling biases and underscore the need for population structure-aware methods and more diverse datasets to improve AMR prediction and surveillance.

During career advancement and funding allocation decisions in biomedicine, reviewers have traditionally depended on journal-level measures of scientific influence like the impact factor. Prestigious journals reject large quantities of papers, many of which may be meritorious. It is possible that this process could create a system whereby some influential articles are prospectively identified and recognized by journal brands, but most influential articles are overlooked. Here, we measure the degree to which journal prestige hierarchies capture or overlook influential science. We quantify the fraction of scientists' articles that would receive recognition because (a) they are published in journals above a chosen impact factor threshold, or (b) they are at least as well-cited as articles appearing in such journals. We find that the number of papers cited at least as well as those appearing in high-impact factor journals vastly exceeds the number of papers published in such venues. At the investigator level, this phenomenon extends across gender, racial, and career stage groupings of scientists. We also find that approximately half of researchers never publish in a venue with an impact factor above 15, which, under journal-level evaluation regimes, may exclude them from consideration for opportunities. Many of these researchers publish equally influential work; however, raising the possibility that the traditionally chosen journal-level measures that are routinely considered under decision-making norms, policy, or law, may recognize as little as 10%-20% of this influential work.

Brain aging can cause cognitive and motor disabilities which often correlate with changes in dendritic branch, axon collateral, and synapse numbers. However, from invertebrates to mammals, age-related decline is typically restricted to specific neuron types or brain parts, indicating differential vulnerability. The rules to pinpoint the susceptibility of distinct brain elements to aging remain largely unknown. Here, we combine longitudinal studies with neuroanatomical, electrophysiological, and optophysiological analyses in the Drosophila genetic model to identify aging-susceptible and aging-resilient elements in a sensorimotor circuit that underlies escape. Young and mid-aged flies escape predator-like visual stimuli with a jump followed by flight, but behavioral performance declines with age. Mapping the underlying functional decline into the brain shows that most circuit components are robust against aging and remain functional even in old flies that have lost the behavior. By contrast, behavioral decline is caused by the selective decay of synaptic transmission between one specific visual projection neuron type (LC4) and the dendrite of one identified descending neuron (GF). Structurally, presynaptic active zone marker density is reduced whereas postsynaptic marker density remains normal. Other central synapses in this circuit as well as neuromuscular synapses are robust to aging. The synaptic connection susceptible to aging is also the circuit element most vulnerable to starvation or oxidative stress. Moreover, the vulnerable circuit element is also required for habituation, and thus, underlying circuit plasticity. In conjunction with data from mammalian brains our data suggest that a trade-off for functional neural circuit plasticity might be vulnerability to aging.

Single-cell RNA sequencing (scRNA-seq) requires high sensitivity, throughput, and broad compatibility across specimens. Current high-capacity methods lack sensitivity compared to low-capacity counterparts. Moreover, tissue-specific methods for collecting cells/nuclei limit unbiased comparisons across samples. Here, we propose a Unified framework by Split-Pool barcoding with optimal-efficiency PolydeoxyAdenylation for scRNA detection (USPPAR). Using short and long dsDNA substrates, low Co²⁺ concentration, while eliminating all other metal-ion components, enabled terminal deoxynucleotide transferase to efficiently polydeoxyadenylate intractable blunt and 3' recessed dsDNA ends, which was unattainable with other systems. By benchmarking against six state-of-the-art technologies using HEK293, the efficient addition of PCR handles for cDNA amplification made USPPAR's gene detection sensitivity comparable to high-sensitivity methods and significantly higher than existing high-cell-capacity platforms. In primary PBMCs, USPPAR enabled high-sensitivity, high-resolution scRNA-seq, and lysine conjugation improved sensitivity as an RNase inactivator. Based on nuclease reporter and mRNA protection assays, partially chelated Cu²⁺ served as a potent, non-precipitating, broad-spectrum nuclease inhibitor across various pH levels. Beyond demonstrating high sensitivity in liver tissue, an organ with low nuclease activity, single-nucleus RNA sequencing (snRNA-seq) with this inhibitor enabled one-pot extraction of RNA-stable nuclei from nuclease-rich tissues, such as the pancreas. Finally, comparisons with reference datasets from the 10× platform using mouse spleen and maize tissues showed that USPPAR matched cell-type coverage while achieving higher gene-detection efficiency. With five key enzymes available and quality-controlled, USPPAR provides a unified, cost-effective, sensitive method for high-cell-capacity scRNA profiling of diverse specimens without special equipment.

Despite early assumptions of neutrality, numerous mechanisms are now thought to cause selection on synonymous mutations, commonly supported by a low evolutionary rate at synonymous sites (Ks). This has been best evidenced in the first ~10 codons of genes in E. coli, where Ks is less than around half that of the gene body. Diverse lines of evidence support the hypothesis that these first ~10 codons are under selection for high AT content which causes low mRNA stability that in turn enables ribosomal initiation. There remains one enigmatic discrepancy, however, namely that the low Ks domain extends far beyond the first 10 codons. Here we ask why this is. As we see no evidence that the zone influencing protein levels has been misestimated, we consider three further hypotheses: that reduced Ks is a) owing to overlapping genes, b) reflects an extended slow translational "ramp," and c) is mutational. We reject the first two as in both E. coli and Bacillus sp. the extended low Ks domain persists on analysis of non-overlapping genes and in Bacillus, where fast optimal codons tend to be A/T-ending, a fast-to-slow codon trend is seen. We fail to falsify the third hypothesis. Employing mutation accumulation data for E. coli we show that the 5' end has a lower mutation rate, with the first 10 codons having a rate around half that of the gene body, this then steadily increasing following the trend seen for Ks. Compositional variation is likely to explain some of the difference, the 5' end lacking GC-rich runs while these are most mutagenic. We conclude that even a highly reduced Ks is not always adequate to substantiate selection on synonymous mutations. This result has broad implications for inference of the causes of evolutionary rate variation.

Red blood cell production is one of the most dynamic processes, yet the underlying mechanisms responsible are only partially understood. A new study in PLOS Biology suggests a broadly applicable mechanism able to balance the maintenance of the steady-state and effective stress response.

The liver's regenerative capacity is underscored by the plasticity potential of adult hepatocytes. In this context, hepatocyte-to-cholangiocyte transdifferentiation (HCT) has been ascribed with pro-regenerative functions in animal models and is a feature of end-stage human chronic liver diseases. While dampened activities of hepatocyte identity transcription factors (TFs) underlay HCT, how the cholangiocyte transcriptional program is implemented is poorly defined. Here, we identify that HCT does not involve transitioning through a hepatoblast-like transcriptional program. Furthermore, we show that HCT primarily involves induction of the archetypal transcriptional program of monopolarized epithelial cells initially repressed in hepatocytes. Indeed, HCT requires relieving H3K27me3-mediated and polycomb-dependent epigenetic silencing of epithelial TF encoding genes including Grainyhead Like Transcription Factor 2 (GRHL2). Ectopic expression of GRHL2 in hepatocytes, including in vivo in the adult mouse liver, induces epithelial genes reminiscent of those activated during HCT. Finally, GRHL2 is detected in human hepatocytes undergoing HCT as evidenced using samples from end-stage chronic liver diseases. Hence, HCT is a process chiefly characterized by induction of a conventional epithelial transcriptional program originally lacking in hepatocytes promoted by derepression of the master epithelial TF GRHL2.