Biology subjects

Holl, J.

Publications and source records attributed to Holl, J..

4 recordsLinked to original sources

bioRxiv2026

Visualizing zinc-starved slow-replicating Mycobacterium tuberculosis in neutrophil-rich lung lesions

The months-long treatment for tuberculosis is partially attributed to a minor Mycobacterium tuberculosis (Mtb) subpopulation exhibiting phenotypic drug resistance, although origins of these bacilli in hosts remain unknown. Previously, we observed that mycobacteria respond to growth-restrictive limitations of zinc by accumulating Mrf, and inducing Mpy recruitment to the decoding center of the ribosome, thereby hibernating the ribosome in an inactive state. Mrf accumulation - regulated at both transcriptional and post-translational levels by Zur and Clp, respectively, in a zinc-dependent manner - facilitates the formation of stable Mpy-70S ribosome complex in zinc-starved cells. Here, using a translational fusion of Mrf with a fluorescent-reporter protein we visualized zinc-starved mycobacteria with a physiology conducive for Mpy-dependent ribosome hibernation. About half of zinc-starved mycobacterial population expressed microscopically detectable levels of the reporter and exhibited Mpy-dependent slowdown of growth and isoniazid tolerance in vitro. In chronic, high-burden mouse lung infections, ~3% of Mtb bacilli expressed the reporter, and the frequency increased to ~35% upon isoniazid treatment. Transcriptomics of mouse lungs suggests an important role of S100A8/A9 and ZIP2 in neutrophils in zinc mobilization during Mtb infections. Moreover, depletion of neutrophils, or loss of S100A9 caused significant attenuation of zinc starvation response in Mtb. Altogether, the study offers a new approach for visualizing and manipulating slow-replicating Mtb in host tissues.

microbiology↗

bioRxiv2025

Integrating Longitudinal Metabolite Profiles Improves Trait Prediction in Pigs in a Trait- and Timepoint-Dependent Manner

BackgroundAccurate prediction of genetic merit is essential for accelerating genetic improvement in pigs, particularly for traits that are costly or difficult to measure directly. This study investigated the potential of integrating individual-level blood serum metabolite profiles sampled at two developmental stages (10-week and 20-week) into genomic prediction models for five economically important traits: average daily feed intake (DFI), feed conversion ratio (FCR), backfat thickness (BF), test daily gain (TDG), and loin depth (LD). Using a BayesC modeling framework, we analyzed 1,637 pigs from a single purebred population with complete phenotype, genotype, and metabolite-profile data. We evaluated seven models, including a genotype-only model (G), metabolite-only models using metabolite-profile data from 10-week (M1), 20-week (M2), or both timepoints (M1+M2), and combined models integrating genotypes with metabolite-profile data (G+M1, G+M2, G+M1+M2). ResultsHeritability estimates were generally low to moderate, ranging from 0.07 to 0.30 for the 10-week metabolite profile and from 0.04 to 0.28 for the 20-week metabolite profile. Prediction accuracy of phenotype consistently improved when metabolite-profile data were integrated into genotype-based models, although the magnitude of improvement varied depending on the trait and the timepoint of metabolite sampling. Prediction accuracy increased from 0.31 (G) to 0.41 (G+M2; G+M1+M2) for DFI, and from 0.27 (G) to 0.33 (G+M2; G+M1+M2) for FCR. The latter two models also delivered the largest gains over G for BF (from 0.41 to 0.45) and TDG (from 0.28 to 0.32). However, LD benefited the most when both 10-week and 20-week metabolite profiles were combined (G+M1+M2: 0.45 compared to G: 0.42). ConclusionsAcross all traits, models combining genotype data with metabolite profiles from one or multiple timepoints achieved the highest or equally high prediction accuracies compared to the genotype-only model, reflecting complementary biological insights captured by metabolite profiles. These findings highlight the potential value of metabolite-profile data as an intermediate omics layer to enhance genomic prediction, particularly when integration strategies are tailored to trait-specific biology and sampling timepoints.

genetics↗

bioRxiv2025

Genetic parameters and genome-wide association analysis of service sire effect on litter size and its relationship with boar semen quality in three terminal sire lines

This study aimed to estimate the genetic parameters for service sire effects on the number born alive (NBA) and its relationship with semen quality traits. Data of 6,416, 23,188, and 48,890 litter size records collected between 2020 and 2024 from three purebred terminal sire lines were analyzed. The number of sows was 3,071, 11,819, and 24,089, with 197, 554, and 891 service sires for the three respective lines. There were 1,424,858, 4,344,630, and 2,146,583 animals in the pedigree of which 67,990, 259,250, and 365,392 were genotyped and imputed up to 50K SNPs. The service sire and dam effects were modeled as additive genetic effects, considering a covariance structure among them, given by the relationship matrix. The model also included fixed effects of contemporary group and parity group with random permanent environmental effects for service sire and dam. Genetic parameters were estimated using the AIREML option in the BLUPF90+ software, and GEBVs were generated by ssGBLUP with the algorithm for proven and young (APY). Heritability for the service sire effect ranged from 0.01 to 0.03, and the heritability for the dam effect ranged from 0.09 to 0.15, with genetic correlations ranging from -0.20 to 0.37. A single-step genome-wide association study (ssGWAS) was also performed, and no strong signals were detected for service sire effects on NBA. Sperm motility (MOT) and total abnormal morphology (ABN_MOR) GEBVs from the three lines were estimated based on about 57,500 to 608,996 ejaculates recorded using the computer-assisted semen analysis (CASA) system from 1,698 to 29,095 boars collected from 2013 to 2025. Heritability estimates ranged from 0.10 to 0.12 for motility and from 0.17 to 0.28 for total abnormal morphology. The correlations between service sire GEBV for NBA and semen quality were low but in the favorable direction. Results suggest that although paternal genetic contributions to litter size were small compared to maternal genetic contributions, selecting on service sire effects on litter size in addition to semen quality traits will improve overall reproductive success.

genetics↗

bioRxiv2020

AlphaPart - R implementation of the method for partitioning genetic trends

BackgroundIn this paper we present the AlphaPart R package, an open-source software that implements a method for partitioning breeding values and genetic trends to identify sources of genetic gain. Breeding programmes improve populations for a set of traits, which can be measured with a genetic trend calculated from averaged year of birth estimated breeding values of selection candidates. While sources of the overall genetic gain are generally known, their realised contributions are hard to quantify in complex breeding programmes. The aim of this paper is to present the AlphaPart R package and demonstrate it with a simulated pig breeding example. ResultsThe package includes the main partitioning function AlphaPart, that partitions the breeding values and genetic trends by analyst defined paths, and a set of functions for handling data and results. The package is freely available from CRAN repository at http://CRAN.R-project.org/package=AlphaPart. We demonstrate the use of the package by examining the genetic gain in a pig breeding example, in which the multiplier achieved higher breeding values than the nucleus for traits measured and selected in the multiplier. The partitioning analysis revealed that these higher values depended on the accuracy and intensity of selection in the multiplier and the extent of gene flow from the nucleus. For traits measured only in the nucleus, the multiplier achieved comparable or smaller genetic gain than the nucleus depending on the amount of gene flow. ConclusionsAlphaPart implements a method for partitioning breeding values and genetic trends and provides a useful tool for quantifying the sources of genetic gain in breeding programmes. The use of AlphaPart will help breeders to better understand or improve their breeding programmes.

genomics↗