Biology subjects

Bader, J. S.

Publications and source records attributed to Bader, J. S..

15 recordsLinked to original sources

bioRxiv2026

Early tuberculosis treatment remodels blood mRNA and small RNA, and a baseline host signature is associated with early culture conversion

Tuberculosis (TB) treatment monitoring relies on sputum-based microbiological assays, which are slow and provide limited insight into the host response. Blood-based biomarkers could offer rapid and minimally invasive treatment monitoring. We performed an integrative multi-omics analysis of paired whole-blood samples collected at baseline and four weeks after treatment initiation across three South African cohorts. A meta-analysis combined RNA sequencing data from GSE89403 (86 pairs) and a prospective cohort (11 pairs), with directional concordance assessed in an independent microarray cohort, GSE31348 (27 pairs). In the prospective cohort, small RNA sequencing profiled microRNAs (miRNAs) and tRNA-derived fragments (tRFs). In GSE89403 (n = 76), a k-top scoring pairs signature (EARLY5) was developed using leave-one-out cross-validation to predict week-4 sputum culture conversion from baseline samples. The meta-analysis identified 63 concordantly regulated genes. These changes reflected attenuation of neutrophil, inflammatory and complement programs, and deconvolution showed decreased neutrophils with increased T-cell and NK-cell populations. Seven miRNAs and eight nuclear-encoded tRFs changed during treatment, including erythroid-associated miR-144, with computationally identified candidate interactions involving complement genes. EARLY5 identified participants who converted by week 4 with a cross-validated AUC of 0.76 and remained associated with conversion after adjustment for baseline bacterial burden in logistic regression and performed comparably to existing TB signatures. Early TB treatment induces coordinated remodeling of blood mRNA and small RNA profiles. Baseline host transcriptional profiles were associated with early culture conversion after accounting for bacterial burden, supporting further evaluation in independent cohorts.

immunology↗

bioRxiv2025

cpiVAE: Robust and Interpretable Cross-Platform Proteomics Imputation

Large-scale plasma proteomic studies often use different high-throughput affinity platforms, and measurements of the same protein across platforms are often discordant. Discordance hinders cross-study integration. Improving proteomics data integration would enable more powerful meta-analyses, improve statistical power for biomarker discovery, and provide a better understanding of proteome-phenotype relationships. Here we present a cross-platform proteomics imputation variational autoencoder (cpiVAE), a deep generative model for bidirectional imputation of protein abundances between two widely used platforms: Olink and SomaScan. Using a training cohort of paired measurements from the China Kadoorie Biobank (CKB), cpiVAE learns a joint latent representation that enables cross-platform imputation. The cpiVAE method improves benchmarks provided by established methods, k-nearest neighbors (KNN) Weighted Nearest Neighbors (WNN, from Seurat v4). The cpiVAE method achieves up to 30% higher correlation between imputed and true values than KNN and WNN. The cpiVAE method also generalizes well to an independent cohort from the Atherosclerosis Risk in Communities Study (ARIC). Without retraining, cpiVAE maintains high performance compared to benchmarks. Associations of imputed protein levels with clinical phenotypes closely mirror results using the actual measurements and increases power in a meta-analysis scenario. A post-hoc feature importance matrix enables interpretation of this AI model. Protein pair features extracted from cpiVAE have significant overlap with known associations in the Search Tool for the Retrieval of Interacting Genes (STRING) database. In summary, cpiVAE offers an accurate, generalizable, and interpretable solution for cross-platform proteomic imputation, enabling integrated analyses across studies with proteomics measured on different platforms. This user-friendly framework and pre-trained model weights are available under a BSD2 open source license at https://github.com/joelbaderlab/cpiVAE_v1.

bioinformatics↗

bioRxiv2025

The Phosphate-Specific Transport System Gene pstA1 Contributes to Rifampin Tolerance in Mycobacterium tuberculosis

Tuberculosis (TB) caused an estimated 10.8 million new cases and 1.25 million deaths in 2023. Antibiotic tolerance, the ability of bacteria to survive exposure to bactericidal antibiotics without genetic resistance mutations, contributes to the need for prolonged treatment. Targeting antibiotic tolerance mechanisms could promote accelerated clearance of Mycobacterium tuberculosis (Mtb), thereby improving medical adherence. Our previous forward genetic screen for rifampin tolerance genes identified pstA1, which is involved in phosphate-specific import. The ABC-type transporter permease PstA1 has previously been implicated in Mtb virulence, as mutants lacking this gene exhibit defective survival during phosphate limitation in vitro, in infected macrophages, and in immunocompetent mice. The minimum inhibitory concentration (MIC) of rifampin was not altered in a pstA1 deletion mutant ({Delta}pstA1), suggesting this difference in susceptibility is not due to antibiotic resistance. Consistent with a role in rifampin tolerance, time-kill assays revealed a shift in the mean duration of killing (2-log reduction) from 1.6 days in wild-type to 1.0 day in {Delta}pstA1, and complementation partially restored this phenotype. We found that pstA1 is specifically required for Mtb survival in the absence of exogenous inorganic phosphate and is important for adaptation to growth in culture without detergent, and within macrophages in an interferon-{gamma}-dependent manner. Differential expression analysis revealed that {Delta}pstA1 exhibited substantial transcriptional reprogramming with 58 differentially expressed genes, including altered expression of metabolic, DNA damage repair, and secretory pathways. PstA1 represents a novel drug target, and inhibitors could serve as adjunctive therapies to shorten treatment times, reducing opportunities for drug resistance emergence. ImportanceTuberculosis remains one of the worlds deadliest infectious diseases, causing over a million deaths annually. Current treatment requires months of antibiotic therapy, and poor adherence to these lengthy regimens contributes to the emergence of drug-resistant strains that are increasingly difficult to treat. A major barrier to shorter treatment is antibiotic tolerance, which allows bacteria to survive drug exposure without genetic resistance mutations. This study identifies the phosphate transport component PstA1 as a critical factor enabling Mycobacterium tuberculosis to tolerate the frontline antibiotic rifampin. Bacteria lacking pstA1 are eliminated more rapidly by rifampin, demonstrating that this transporter actively promotes bacterial survival during treatment. These findings suggest that drugs targeting PstA1 could be combined with standard antibiotics to accelerate bacterial clearance, potentially shortening treatment duration and improving patient adherence. Such adjunctive therapies targeting tolerance mechanisms represent a promising strategy to combat tuberculosis and reduce the global burden of drug-resistant disease.

microbiology↗

bioRxiv2025

Random survival forests identify myocardial gene signatures associated with survival in heart failure with preserved ejection fraction

Heart failure with preserved ejection fraction (HFpEF) continues to be poorly understood at the molecular level. While previous studies have identified gene expression signatures unique to HFpEF, genes associated with clinical decompensation have not been determined. Here, we performed exploratory analysis of myocardial RNA-seq data to identify genes associated with event-free survival in HFpEF. We analyzed previously published RNA sequencing data of right ventricular septal endomyocardial biopsies from HFpEF patients (n=41) with paired clinical, echocardiographic, and outcome data (including mortality and heart failure hospitalizations). We constructed random survival forests with forward stepwise regularization (the "variable hunting" method) to determine genes associated with time to first event using a combined end-point of heart failure hospitalization or all-cause death. Selection of candidate forest variables was tested with both random and weighted sampling methods. We identified 33 genes that are predictive of survival in HFpEF. This set includes genes previously implicated in heart failure, including ADAMTSL2, ADRB1, BMP6, and METRNL. Survival forests constructed using these genes outperform those constructed from clinical and hemodynamic parameters alone (out-of-bag C-index 0.894 vs 0.545). Moreover, in survival forests constructed from both gene data and hemodynamic measurements, individual survival genes consistently showed higher variable importance than clinical/hemodynamic parameters. Our study shows that random survival forests identify myocardial gene signatures that may better model HFpEF prognosis than clinical measurements. Further studies are warranted to validate findings in independent cohorts.

genomics↗

bioRxiv2022

Polymer physics of structural evolution in synthetic yeast chromosomes

Yeast SCRaMbLE is an experimental method using designed synthetic yeast chromosomes to generate combinatorial diversity through genome rearrangements. These events occur at designed loxPsym recombination sites through the activity of Cre recombinase. While the synthetic SCRaMbLE system was designed to explore minimal genomes and permit rapid genome evolution, the pattern of recombinations also reflects inherent properties of DNA looping required to coalesce pairs of loxPsym sites. Genomes of yeast strains generated by SCRaMbLE are analyzed here using a new statistical mechanics model, called the SCRaMbLE Polymer Interaction (SPI) model. SPI uses polymer physics to model recombinations, and implements efficient rejection sampling and histogram reweighting algorithms to conduct SCRaMbLE experiments in silico. Using SPI, we found that recombination events observed experimentally are consistent with a random walk scaling exponent ranging between 0.45 and 0.6, which spans values of 0.5 for a Gaussian polymer and 0.588 for a self-avoiding walk. SPI provides a highly accurate tool to study SCRaMbLE recombinations and massively parallel genome recombination experiments.

synthetic biology↗

bioRxiv2022

Next-generation large-scale binary protein interaction network for Drosophila

Generating reference maps of the interactome networks underlying most cellular functions can greatly illuminate genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. Here, we applied state-of-the-art experimental and bioinformatics methods to identify high-confidence binary protein-protein interactions (PPIs) for Drosophila melanogaster. We performed four all-by-all yeast two-hybrid (Y2H) screens of >10,000 Drosophila proteins, resulting in the FlyBi dataset of 8,723 PPIs among 2,939 proteins. As part of this effort, we tested subsets of our data and data from previous PPI datasets using an orthogonal assay, which allowed us to normalize data quality across datasets. Next, we integrated our FlyBi data with previous PPI data, resulting in an expanded, high-confidence binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6,511 proteins. These data are accessible through the Molecular Interaction Search Tool (MIST) and other databases. To assess the utility of the PPI resource, we used novel interactions from the FlyBi dataset to generate an autophagy interaction network that we validated in vivo using two different autophagy-related assays. We found that deformed wings (dwg) encodes a protein that is both a regulator and a target of autophagy. Altogether, the resources generated in this project provide a strong foundation for building high-confidence new hypotheses regarding protein networks and function.

cell biology↗

bioRxiv2022

Laboratory evolution and polyploid SCRaMbLE reveal genomic plasticity to synthetic chromosome defects and rearrangements

We have designed, constructed, and debugged a synthetic 753,096 bp version of Saccharomyces cerevisiae chromosome XIV as part of the international Sc2.0 project. We showed that certain synthetic loxPsym recombination sites can interfere with mitochondrial protein localization, that the deletion of one intron (NOG2) reduced fitness, and that a reassigned stop codon can lead to a growth defect. In parallel to these rational debugging modifications, we used Adaptive Laboratory Evolution to generate a general growth defect suppressor rearrangement in the form of increased TAR1 copy number. We also extended the utility of the Synthetic Chromosome Recombination and Modification by LoxP-mediated Evolution (SCRaMbLE) system by engineering synthetic-wild-type tetraploid hybrid strains that buffer against essential gene loss. The presence of wild-type chromosomes in the hybrid tetraploids increased post-SCRaMbLE viability and heterologous DNA integration, highlighting the plasticity of the S. cerevisiae genome in the presence of rational and non-rational modifications.

synthetic biology↗

bioRxiv2022

Synthetic yeast chromosome XI design enables extrachromosomal circular DNA formation on demand

We describe construction of the 660 kilobase synthetic yeast chromosome XI (synXI) and reveal how synthetic redesign of non-coding DNA elements impact the cell. To aid construction from synthesized 5 to 10 kilobase DNA fragments, we implemented CRISPR-based methods for synthetic crossovers in vivo and used these methods in an extensive process of bug discovery, redesign and chromosome repair, including for the precise removal of 200 kilobases of unexpected repeated sequence. In synXI, the underlying causes of several fitness defects were identified as modifications to non-coding DNA, including defects related to centromere function and mitochondrial activity that were subsequently corrected. As part of synthetic yeast chromosome design, loxPsym sequences for Cre-mediated recombination are inserted between most genes. Using the GAP1 locus from chromosome XI, we show here that targeted insertion of these sites can be used to create extrachromosomal circular DNA on demand, allowing direct study of the effects and propagation of these important molecules. Construction and characterization of synXI has uncovered effects of non-coding and extrachromosomal circular DNA, contributing to better understanding of these elements and informing future synthetic genome design.

synthetic biology↗

bioRxiv2020

Transcriptome Analysis of Human Induced Excitatory Neurons Supports a Strong Effect of Clozapine on Cholesterol Biosynthesis

Antipsychotics are known to modulate dopamine and other neurotransmitters which is often thought to be the mechanism underlying their therapeutic effects. Nevertheless, other less studied consequences of antipsychotics on neuronal function may contribute to their efficacy. Revealing the complete picture behind their action is of paramount importance for precision medicine and accurate drug selection. Progress in cell engineering allows the generation of induced pluripotent stem cells (iPSCs) and their differentiation to a variety of neuronal types, providing new tools to study antipsychotics. Here we use excitatory cortical neurons derived from iPSCs to explore their response to therapeutic levels of Clozapine as measured by their transcriptomic output, a proxy for neuronal homeostasis. To our surprise, but in agreement with the results of many investigators studying glial-like cells, Clozapine had a very strong effect on cholesterol metabolism. More than a quarter (12) of all annotated cholesterol genes (46) in the genome were significantly changed at FDR<0.1, all upregulated. This is a 35-fold enrichment with an adjusted p = 8 x10-11. Notably no other functional category showed evidence of enrichment. Cholesterol is a major component of the neuronal membrane and myelin but it does not cross the blood brain barrier, it is produced locally mostly by glia but also by neurons. By singling out increased expression of cholesterol metabolism genes as the main response of cortical excitatory neurons to antipsychotics, our work supports the hypothesis that cholesterol metabolism may be a contributing mechanism to the beneficial effects of Clozapine and possibly other antipsychotics

neuroscience↗

bioRxiv2020

A mediation analysis of schizophrenia variants: Risk alleles may affect a gene's expression differently from how the expression affects risk

Variants identified by genome-wide association studies (GWAS) are often expression quantitative trait loci (eQTLs), suggesting they are proxies or are themselves regulatory. Across many datasets analyses show that variants often affect multiple genes. Lacking data on many tissue types, developmental time points and homogeneous cell types, the extent of this one-to-many relationship is underestimated. This raises questions on whether a disease eQTL target gene explains the genetic association or is a by-stander and puts into question the direction of expression effect of on the risk, since the many variant - regulated genes may have opposing effects, imperfectly balancing each other. We used two brain gene expression datasets (CommonMind and BrainSeq) for mediation analysis of schizophrenia-associated variants. We confirm that eQTL target genes often mediate risk but the direction in which expression affects risk is often different from that in which the risk allele changes expression. Of 38 mediator genes significant in both datasets 33 showed consistent mediation direction (Chi2 test P=6*10-6). One might expect that the expression would correlate with the risk allele in the same direction it correlates with disease. For 15 of these 33 (45%), however, the expression change associated with the risk allele was protective, suggesting the likely presence of other target genes with overriding effects. Our results identify specific risk mediating genes and suggest caution in interpreting the biological consequences of targeted modifications of gene expression, as not all eQTL targets may be relevant to disease while those that are, might have different than expected directions.

genetics↗

bioRxiv2019

The paltry power of priors versus populations

Genome-wide tests, including genome-wide association studies (GWAS) of germ-line genetic variants, driver tests of cancer somatic mutations, and transcriptome-wide association tests of RNA-Seq data, carry a high multiple testing burden. This burden can be overcome by enrolling larger cohorts or alleviated by using prior biological knowledge to favor some hypotheses over others. Here we compare these two methods in terms of their abilities to boost the power of hypothesis testing. We provide a quantitative estimate for progress in cohort sizes, and present a theoretical analysis of the power of oracular hard priors: priors that select a subset of hypotheses for testing, with an oracular guarantee that all true positives are within the tested subset. This theory demonstrates that for GWAS, strong priors that limit testing to 100-1000 genes provide less power than typical annual 20-40% increases in cohort sizes. These theoretical results explain the continued dominance of simple, unbiased univariate hypothesis tests for RNA-Seq studies and GWAS: if a statistical question can be answered by larger cohort sizes, it should be answered by larger cohort sizes rather than by more complicated biased methods involving priors. We suggest that priors are better suited for non-statistical aspects of biology, such as pathway structure and causality, that are not yet easily captured by standard hypothesis tests. Author summaryBiological experiments often test thousands to millions of hypotheses. Gene-based tests for human RNA-Seq data, for example, involve approximately 20,000 tests; genome-wide association studies (GWAS) involve about 1 million effective tests. A robust approach is to perform individual tests and then apply a Bonferroni correction to account for multiple testing. This approach implies a single-test p-value of 2.5 x 10-6 for RNA-Seq experiments, and a p-value of 5 x 10-8 for GWAS, to control the false-positive rate at a conventional value of 0.05. Many methods have been proposed to alleviate the multiple-testing burden by incorporating a prior probability that boosts the significance for a subset of candidate genes or variants. At the extreme limit, only hypotheses within a candidate set are tested, corresponding to a decreased multiple testing burden. Despite decades of methods development, prior-based tests have not been generally used. Here we compare the power increase possible with a prior with the power increase from a much simpler strategy of increasing a study size. We show that increasing the population size is exponentially more valuable than increasing the strength of prior, even when the true prior is known exactly. Furthermore, even modest yearly increases in actual GWAS cohorts can yield power gains beyond the reach of any reasonable prior. These results provide a rigorous explanation for the continued use of simple, robust methods rather than more sophisticated approaches. They suggest that the value of priors is not in multiple hypothesis testing but rather in non-statistical aspects of interpretation including pathway structure and causality.

genetics↗

bioRxiv2019

BRCA1 Mediated Homologous Recombination and S Phase DNA Repair Pathways Restrict LINE-1 Retrotransposition in Human Cells

Long interspersed element-1 (LINE-1 or L1) is the only autonomous retrotransposon active in human cells. L1s DNA makes about 17% of the human genome and retrotransposition of a few active L1 copies has been detected in various tumors, underscoring the potential role of L1 in mediating or increasing genome instability during tumorigenic development. Different host factors have been shown to influence L1 mobility through several mechanisms. However, systematic analyses of host factors affecting L1 retrotransposition are limited. Here, we developed a high-throughput microscopy-based retrotransposition assay and coupled it to a genome-wide siRNA knockdown screen to study the cellular regulators of L1 retrotransposition in human cells. We showed that L1 insertion frequency was stimulated by knockdown of Double-Stranded Break (DSB) repair factors that are active in the S/G2 phase of the cell cycle including Homologous Recombination (HR), Fanconi Anemia (FA) and, to a less extent, microhomology-mediated end-joining (MMEJ) factors. In particular, we show that BRCA1, an E3 ubiquitin ligase with a key role in several DNA repair pathways, plays multiple roles in regulating L1; BRCA1 knockdown directly affects L1 retrotransposition frequency and structure and also plays a role in controlling L1 ORF2 protein translation through L1 mRNA binding. These results suggest the existence of a \"battle\" between HR factors and L1 retrotransposons, revealing a potential role for L1 in development of tumors characterized by BRCA1 and HR repair deficiencies.

cell biology↗

bioRxiv2018

Synthetic chromosome fusion: effects on genome structure and function

As part of the Synthetic Yeast 2.0 (Sc2.0) project, we designed and synthesized synthetic chromosome I. The total length of synI is [~]21.4% shorter than wild-type chromosome I, the smallest chromosome in Saccharomyces cerevisiae. SynI was designed for attachment to another synthetic chromosome due to concerns of potential instability and karyotype imbalance. We used a variation of a previously developed, robust CRISPR-Cas9 method to fuse chromosome I to other chromosome arms of varying length: chrIXR (84kb), chrIIIR (202kb) and chrIVR (1Mb). All fusion chromosome strains grew like wild-type so we decided to attach synI to synIII. Through the investigation of three-dimensional structures of fusion chromosome strains, unexpected loops and twisted structures were formed in chrIII-I and chrIX-III-I fusion chromosomes, which depend on silencing protein Sir3. These results suggest a previously unappreciated 3D interaction between HMR and the adjacent telomere. We used these fusion chromosomes to show that axial element Red1 binding in meiosis is not strictly chromosome size dependent even though Red1 binding is enriched on the three smallest chromosomes in wild-type yeast, and we discovered an unexpected role for centromeres in Red1 binding patterns.

synthetic biology↗

bioRxiv2018

Discovering patterns of pleiotropy in genome-wide association studies

MotivationGenome-wide association studies have had great success in identifying human genetic variants associated with disease, disease risk factors, and other biomedical phenotypes. Many variants are associated with multiple traits, even after correction for trait-trait correlation. Discovering subsets of variants associated with a shared subset of phenotypes could help reveal disease mechanisms, suggest new therapeutic options, and increase the power to detect additional variants with similar pattern of associations. Here we introduce two methods based on a Bayesian framework, SNP And Pleiotropic PHenotype Organization (SAPPHO), one modeling independent phenotypes (SAPPHO-I) and the other incorporating a full phenotype covariance structure (SAPPHO-C). These two methods learn patterns of pleiotropy from genotype and phenotype data, using identified associations to discover additional associations with shared patterns.\n\nResultsThe SAPPHO methods, along with other recent approaches for pleiotropic association tests, were assessed using data from the Atherosclerotic Risk in Communities (ARIC) study of 8,000 individuals, whose gold-standard associations were provided by meta-analysis of 40,000 to 100,000 individuals from the CHARGE consortium. Using power to detect gold-standard associations at genome-wide significance (0.05 family-wise error rate) as a metric, SAPPHO performed best. The SAPPHO methods were also uniquely able to select the most significant variants in a parsimonious model, excluding other less likely variants within a linkage disequilibrium block. For meta-analysis, the SAPPHO methods implement summary modes that use sufficient statistics rather than full phenotype and genotype data. Meta-analysis applied to CHARGE detected 16 additional associations to the gold-standard loci, as well as 124 novel loci, at 0.05 false discovery rate. Reasons for the superior performance were explored by performing simulations over a range of scenarios describing different genetic architectures. With SAPPHO we were able to learn genetic structures that were hidden using the traditional univariate tests.\n\nAvailabilityhttps://bitbucket.org/baderlab/fast/wiki/Home. SAPPHO software is available under the GNU General Public License, v2.

genetics↗

bioRxiv2018

Genome-wide association meta-analysis of PR interval identifies 47 novel loci associated with atrial and atrioventricular electrical activity

Electrocardiographic PR interval measures atrial and atrioventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. We performed a genome-wide association study in over 92,000 individuals of European descent and identified 44 loci associated with PR interval (34 novel). Examination of the 44 loci revealed known and novel biological processes involved in cardiac atrial electrical activity, and genes in these loci were highly over-represented in several cardiac disease processes. Nearly half of the 61 independent index variants in the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with one or more missense variants. Cardiac regulatory regions of the genome as measured by cardiac DNA hypersensitivity sites were enriched for variants associated with PR interval, compared to non-cardiac regulatory regions. Joint analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation identified additional new pleiotropic loci. The majority of associations discovered in European-descent populations were also present in African-American populations. Meta-analysis examining over 105,000 individuals of African and European descent identified additional novel PR loci. These additional analyses identified another 13 novel loci. Together, these findings underscore the power of GWAS to extend knowledge of the molecular underpinnings of clinical processes.

genetics↗