Biology subjects

Bach, E.

Publications and source records attributed to Bach, E..

6 recordsLinked to original sources

bioRxiv2025

Age-related declines in niche self-renewal factors controls testis aging and spermatogonial stem cell competition through Hairless, Imp, and Chinmo

Aging is associated with progressive tissue decline and shifts in stem cell clonality. The role of niche signals in driving these processes remains poorly understood. Using the Drosophila testis, we identify a regulatory axis in which age-related decline of niche signals (BMPs) lead to upregulation of the co-repressor Hairless, which downregulates the RNA-binding protein Imp in aged germline stem cells (GSCs). Reduced Imp causes loss of Chinmo, a key factor in GSC aging and competition. Reduced Chinmo causes ectopic Perlecan secretion which accumulates in the testis lumen and causes GSC loss. Aging of the testis is reversed by increasing BMPs in the niche, or by overexpressing Imp or depleting Hairless in GSCs. Furthermore, GSC clones with reduced Imp or increased Hairless are more competitive, expelling wild-type neighbors and monopolizing the niche. Thus, BMPs regulate testicular niche aging through the Hairless-Imp-Chinmo axis and "winning" GSCs usurp these aging mechanisms. HighlightsO_LIAged niche cells produce less BMPs, resulting in more Hairless (H) in aged GSCs C_LIO_LIElevated H represses Imp, resulting in less Chinmo and in ectopic ECM secretion C_LIO_LIAging is prevented by higher BMP in niche cells, or by higher Imp or lower H in GSCs C_LIO_LIGSCs with low Imp or high H exploit these aging mechanisms to colonize the GSC pool C_LI

genetics↗

bioRxiv2025

The pioneer factor Zelda induces male-to-female somatic sex reversal in adult tissues

Somatic sex identity must be maintained throughout adulthood for tissue function. Adult somatic stem cells in the Drosophila testis (i.e., CySCs) lacking the transcription factor Chinmo are reprogrammed to their ovarian counterparts by induction of female-specific TraF, but this is not mechanistically understood. Pioneer factors play central roles in direct reprogramming, and many upregulated genes in chinmo-/- CySCs contain binding sites for the pioneer factor Zelda (Zld). microRNAs repress zld mRNA in wild type CySCs, but they are downregulated after Chinmo loss, allowing for zld mRNA translation. Zld depletion from chinmo-/- CySCs suppresses feminization, and ectopic Zld induces TraF and feminizes wild-type CySCs. qkr58E-2 and ecdysone receptor (EcR), direct Zld targets in the embryo, are female-biased in adult gonads and upregulated in chinmo-/- CySCs. The RNA-binding protein Qkr58E-2 produces TraF, while EcR promotes female-biased gene expression. Ectopic Zld feminizes adult male adipose tissue, demonstrating that Zld can instruct female and override male identity in adult XY tissues. HighlightsO_LIzld mRNA is repressed by microRNAs in XY somatic gonadal cells C_LIO_LIZld is upregulated in and required for sex reversal of XY chinmo-/- cells C_LIO_LIZld induces Qkr58E-2 and EcR, which cause TraF and female-biased transcription C_LIO_LIZld feminizes XY adipose cells by inducing TraF and downregulating Chinmo C_LI

developmental biology↗

bioRxiv2024

Profiling of linear B-cell epitopes against human coronaviruses in pooled sera sampled early in the COVID-19 pandemic

BackgroundAntibodies play a key role in the immune defence against infectious pathogens. Understanding the underlying process of B cell recognition is not only of fundamental interest; it supports important applications within diagnostics and therapeutics. Whereas the nature of conformational B cell epitope recognition is inherently complicated, linear B cell epitopes offer a straightforward approach that potentially can be reduced to one of peptide recognition. MethodsUsing an overlapping peptide approach representing the entire proteomes of the seven main coronaviruses known to infect humans, we analysed sera pooled from eight PCR-confirmed COVID-19 convalescents and eight pre-pandemic controls. Using a high-density peptide microarray platform, 13-mer peptides overlapping by 11 amino acids were in situ synthesised and incubated with the pooled primary serum samples, followed by development with secondary fluorochrome-labelled anti-IgG and -IgA antibodies. Interactions were detected by fluorescence detection. Strong Ig interactions encompassing consecutive peptides were considered to represent "high-fidelity regions" (HFRs). These were mapped to the coronavirus proteomes using a 60% homology threshold for clustering. ResultsWe identified 333 human coronavirus derived HFRs. Among these, 98 (29%) mapped to SARS-CoV-2, 144 (44%) mapped to one or more of the four circulating common cold coronaviruses (CCC), and 54 (16%) cross-mapped to both SARS-CoV-2 and CCCs. The remaining 37 (11%) mapped to either SARS-CoV or MERS-CoV. Notably, the COVID-19 serum was skewed towards recognising SARS-CoV-2-mapped HFRs, whereas the pre-pandemic was skewed towards recognising CCC-mapped HFRs. In terms of absolute numbers of linear B cell epitopes, the primary targets are the ORF1ab protein (60%), the spike protein (21%), and the nucleoprotein (15%) in that order; however, in terms of epitope density the order would be reversed. ConclusionWe identified linear B cell epitopes across coronaviruses, highlighting pan-, alpha-, beta-, or SARS-CoV-2-corona-specific B cell recognition patterns. These findings could be pivotal in deciphering past and current exposures to epidemic and endemic coronavirus. Moreover, our results suggest that pre-pandemic anti-CCC antibodies may cross-react against SARS-CoV-2, which could explain the highly variable outcome of COVID-19. Finally, the methodology used here offers a rapid and comprehensive approach to high-resolution linear B-cell epitope mapping, which could be vital for future studies of emerging infectious diseases.

immunology↗

bioRxiv2023

A cascade of sulfur transferases delivers sulfur to the sulfur-oxidizing heterodisulfide reductase-like complex

A heterodisulfide reductase-like complex (sHdr) and novel lipoate-binding proteins (LbpAs) are central players of a wide-spread pathway of dissimilatory sulfur oxidation. Bioinformatic analysis demonstrate that the cytoplasmic sHdr-LbpA systems are always accompanied by sets of sulfur transferases (DsrE proteins, TusA, rhodaneses). The exact composition of these sets may vary depending on the organism and sHdr system type. To enable generalizations, we studied model sulfur oxidizers from distant bacterial phyla, i.e. Aquificota and Pseudomonadota. DsrE3C of the chemoorganotrophic Alphaproteobacterium Hyphomicrobium denitrificans and DsrE3B from the Gammaproteobacteria Thioalkalivibrio sp. K90mix, an obligate chemolithotroph, and Thiorhodospira sibirica, an obligate photolithotroph, are homotrimers that donate sulfur to TusA. Additionally, the hyphomicrobial rhodanese-like protein Rhd442 exchanges sulfur with both TusA and DsrE3C. The latter is essential for sulfur oxidation in Hm. denitrificans. TusA from Aquifex aeolicus (AqTusA) interacts physiologically with AqDsrE, AqLbpA and AqsHdr proteins. This is particularly significant as it establishes a direct link between sulfur transferases and the sHdr-LbpA complex that oxidizes sulfane sulfur to sulfite. In vivo, it is unlikely that there is a strict unidirectional transfer between the sulfur-binding enzymes studied. Rather, the sulfur transferases form a network, each with a pool of bound sulfur. Sulfur flux can then be shifted in one direction or the other depending on metabolic requirements. A single pair of sulfur-binding proteins with a preferred transfer direction, such as a DsrE3-type protein towards TusA, may be sufficient to push sulfur into the sink where it is further metabolized or needed. SIGNIFICANCE STATEMENTA network of bacterial sulfur transferases is uncovered and characterized that ultimately delivers sulfur to a complex cytoplasmic sulfur-oxidizing metalloenzyme, sHdr, that resembles heterodisulfide reductase from methanogenic archaea and interacts with lipoate-binding proteins. Similar sets of sulfur transferases occur in phylogenetically distant bacteria, underscoring the fundamental importance of the work.

biochemistry↗

bioRxiv2022

Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data

We present LC-MS2Struct, a machine learning framework for structural annotation of small molecule data arising from liquid chromatography-tandem mass spectrometry (LC-MS2) measurements. LC-MS2Struct jointly predicts the annotations for a set of mass spectrometry features in a sample, using a novel structured prediction model trained to optimally combine the output of state-of-the-art MS2 scorers and observed retention orders. We evaluate our method on a dataset covering all publicly available reversed phase LC-MS2 data in the MassBank reference database, including 4327 molecules measured using 18 different LC conditions from 16 contributors, greatly expanding the chemical analytical space covered in previous multi-MS2 scorer evaluations. LC-MS2Struct obtains significantly higher annotation accuracy than earlier methods and improves the annotation accuracy of state-of-the-art MS2 scorers by up to 106%. The use of stereochemistry-aware molecular fingerprints improves prediction performance, which highlights limitations in existing approaches and has strong implications for future computational LC-MS2 developments.

bioinformatics↗

bioRxiv2020

Probabilistic Framework for Integration of Mass Spectrum and Retention Time Information in Small Molecule Identification

MotivationIdentification of small molecules in a biological sample remains a major bottleneck in molecular biology, despite a decade of rapid development of computational approaches for predicting molecular structures using mass spectrometry (MS) data. Recently, there has been increasing interest in utilizing other information sources, such as liquid chromatography (LC) retention time (RT), to improve the MS based identifications. ResultsWe put forward a probabilistic modelling framework to integrate MS and RT data of multiple features in an LC-MS experiment. We model the MS measurements and all pairwise retention order information as a Markov random field and use efficient approximate inference for scoring and ranking potential molecular structures. Our experiments show improved identification accuracy by combining tandem mass spectrometry data (MS2) and retention orders using our approach, thereby outperforming state-of-the-art methods. Furthermore, we demonstrate the benefit of our model when only a subset of LC-MS features have MS2 measurements available besides MS1. Availability and implementationSoftware and data is freely available at https://github.com/aalto-ics-kepaco/msms_rt_score_integration. Contacteric.bach@aalto.fi

systems biology↗