Biology subjects

Andrade, M.

Publications and source records attributed to Andrade, M..

18 recordsLinked to original sources

bioRxiv2026

Bloom syndrome helicase is required for efficient HIV-1 reverse transcription in macrophages

The induction of DNA damage by HIV-1 prior to integration suggests a function for DNA damage responses (DDR) during early infection, however what this role is remains incompletely understood. Initial experiments, using specific inhibitors for DDR pathways demonstrate that both ATM and ATR are necessary for efficient HIV-1 infection of macrophages with ATM acting at the late reverse transcription step. To identify DDR factors associated with ATM/ATR pathways that influence HIV-1 infection, a CRISPR knockout screen using a DDR-focused sgRNA library was performed. Approximately 30 DDR genes that impacted HIV-1 infection were identified with 13 factors that facilitated HIV-1 infection and 17 DDR factors that restrict HIV-1 infection. Several hits were factors associated with the Fanconi anemia pathway, such as BTR complex proteins, including the RecQ helicase Bloom syndrome helicase. BLM was specifically demonstrated to enhance HIV-1 infection and replication with knockdown of BLM expression diminishing integration and the establishment of intact HIV-1 proviruses in macrophages by 50%. BLM is associated with HIV-1 late reverse transcription intermediates, the step that proceeds HIV-1 integration. These findings identify BLM as a DDR host factor that promotes early HIV-1 infection by facilitating completion of reverse transcription and subsequent integration. Significance StatementHIV-1 infection elicits cellular DNA damage responses although the role of DNA damage in HIV-1 infection has not been fully characterized. Our study identifies specific DNA Damage factors that facilitate or restrict HIV infection. In particular, we show the RecQ helicase Bloom syndrome helicase (BLM) is a mediator of HIV-1 reverse transcription and integration in macrophages. This work highlights a functional interface between DNA damage repair pathways and HIV-1 integration suggesting that targeting select host DNA damage response factors can limit HIV-1 infection and persistence.

microbiology↗

bioRxiv2026

Cross-Domain Transfer Learning from Peptides to Lipids Using a Multi-Property Fine-Tuned LLM

Accurate knowledge of liquid chromatography retention time (RT) is essential for confident compound identification in metabolomics and lipidomics. Yet, it is often constrained by the scarcity of experimental data for many molecular classes. Current workflows depend on experimental RT libraries, which are time-consuming to build and limited to previously observed compounds. Here, we present a transfer learning pipeline that leverages large, publicly available peptide datasets to enable accurate lipid RT prediction in data-sparse scenarios. We first show that a ChemBERTa language model, when pre-trained on peptides with a multi-task objective (predicting both RT and fundamental RDKit molecular descriptors), learns a more robust and generalizable chemical representation than a single-task (RT-only) model. This multi-property pre-training yielded superior generalization in lipids, achieving test R2 values of 0.842 against 0.814 (RT-only). Crucially, transferring this peptide-based model to lipid data provided a pronounced advantage in data-sparse scenarios. When fine-tuned on only 5% of available lipid data, the transferred model improved the median test R2 by +0.234 over a model trained from scratch. Significant benefits persisted at intermediate data scales (50-75%), with performance converging only when 100% of the lipid data was used. Notably, the pre-trained model never underperformed the baseline, exhibiting more stable training across all data scales. These results demonstrate that multi-property pre-training guides language models towards chemically meaningful representations that support better RT prediction in different molecular domains. Furthermore, peptide-based pre-training facilitates cross-domain transfer of chemical properties to lipid. Our work provides a practical, scalable strategy to mitigate data scarcity in lipidomics by transferring knowledge from data-rich peptide databases, offering a computational alternative to extensive experimental library generation and enabling more confident identification in small-scale omics studies.

bioinformatics↗

bioRxiv2025

Target-site Dynamics and Alternative Polyadenylation Explain Large Share of Apparent MicroRNA Differential Expression

MicroRNA (miRNA) abundance reflects a dynamic balance between biogenesis, target engagement, and decay, yet differential expression analyses typically ignore changes in target-site availability driven by alternative polyadenylation (APA). We introduce MIRNAPEX, an expression-stratification-based machine learning framework that quantifies miRNA regulatory effect sizes from RNA-seq data by integrating target-gene expression with 3'UTR isoform usage to infer effective binding-site dosage. Using pan-cancer training sets, we train models that learn relationships between transcriptomic features and miRNA log-fold changes, with APA patterns providing predictive information beyond gene expression alone. When applied to knockdowns of core APA regulators, MIRNAPEX captured widespread 3'UTR shortening and accurately anticipated miRNA-specific shifts whose direction and magnitude mirrored APA-driven changes in binding-site availability. Analysis of target-directed miRNA degradation interactions further showed that loss of distal decay-trigger sites coincides with increased miRNA abundance, consistent with reduced degradation. Together, these findings demonstrate that apparent miRNA differential expression can arise from dynamic target-site landscapes rather than altered miRNA transcription, and that neglecting this dimension can lead to misestimation of regulatory effect sizes.

bioinformatics↗

bioRxiv2025

Dicer is essential for proper maturation, composition, and function in the postnatal retina.

microRNAs (miRNAs) play a pivotal role during the early phases of retinal development, but their impact on late-phase retinogenesis is unknown. We depleted miRNAs in late retinal progenitor/precursor cells (RPCs/PCs) via a conditional Dicer knock-out. Optical coherence tomography (OCT), electroretinography (ERG), histological, and transcriptional analyses were conducted in young and adult mice. Alterations in gene expression of late-born cells were observed as early as postnatal day 7 (P7), resulting in impaired rod function, a significantly reduced number of rod bipolar cells and their associated function, and a decreased Muller glia population at adult age. These defects appear to be caused by a delay in differentiation/ incomplete maturation, as indicated by an enlarged progenitor/precursor population at young ages that persists into adulthood. Notably, an increased population of HuC/D+ amacrine cells was found. Luciferase assays led us to speculate that this increase may be due to the absence of Elavl3 suppression via RPC-miRNAs. This suggests that Dicer/miRNAs in late RPC/PCs are essential for the proper formation and maturation of late RPC progenies and may also play a role in regulating cell state. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/635135v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@9e0950org.highwire.dtl.DTLVardef@1757e2corg.highwire.dtl.DTLVardef@aeb5ecorg.highwire.dtl.DTLVardef@29accb_HPS_FORMAT_FIGEXP M_FIG C_FIG Summary statementLate-retinal progenitor microRNAs are essential for proper postnatal retinogenesis and retinal function.

developmental biology↗

bioRxiv2025

Unraveling cooperative and competitive interactions within protein triplets in the human interactome

Knowledge about protein-protein interactions (PPIs) is crucial for our understanding of cellular functions. An important contribution to these comes from experimental high-throughput techniques such as yeast two-hybrid (Y2H), which provide evidence for direct, binary PPIs. Consequently, although protein function often emerges from interactions within multi-protein assemblies, most PPI networks focus on binary relationships. Higher-order motifs, such as protein triplets, can reflect cooperative or competitive binding events crucial for cellular function. However, distinguishing these interaction types systematically from a network of binary PPIs remains challenging. To address this issue, we present a computational framework to predict cooperative and competitive interactions among protein triplets in the human Protein Interaction Network (hPIN). By embedding the hPIN into two-dimensional hyperbolic space using the LaBNE+HM algorithm, we extracted latent geometric coordinates for each protein. Combined with topological features and biological annotations, these were used to train a Random Forest classifier on structurally validated triplets from Interactome3D. Our model achieved strong performance (AUC = 0.88), identifying angular and hyperbolic distances as two of the most predictive features. Cooperative triplets were characterized by longer common proteins and a lower frequency of paralogous partners, indicating distinct structural and evolutionary features compared to competitive cases. Structural evaluation using AlphaFold 3 confirmed that cooperative triplets exhibit distinct binding sites, whereas competitive ones share overlapping interfaces. Hyperbolic embeddings, in combination with machine learning, offer a powerful approach to characterize higher-order interaction motifs in protein networks. Our findings provide mechanistic insights into the organization of protein complexes and a predictive framework to support future studies in network biology.

bioinformatics↗

bioRxiv2025

Intra-tumoral delivery of FLT3L with CXCR3/CCR5 ligands promotes XCR1+ DC1 infiltration and activates anti-tumor immunity

Tumor infiltration by XCR1 conventional dendritic cells (cDC1) correlates strongly with favorable prognosis and improved responses to immunotherapy. Yet, tumor-driven immunosuppressive programs restrict efficient cDC1 recruitment, highlighting the need for strategies increasing cDC1 access to the tumor microenvironment. Here, we establish a proof-of-concept cell-based immunotherapy that enhances the infiltration of circulating cDC1 progenitors and supports their local expansion. Intratumoral engraftment of autologous mesenchymal stromal cells engineered to express membrane bound FLT3L promotes cDC1 recruitment when combined with poly(I:C). We identify poly(I:C)-induced CXCL9 and CCL5 as essential chemokines controlling intratumoral cDC1 infiltration. Stromal cell-mediated local delivery of FLT3L together with CXCL9 and CCL5 is sufficient to enhance cDC1 infiltration in mice or humanized mice settings. Finally, this approach activates antitumor immunity and partially overcomes resistance to immune checkpoint blockade. Collectively, our data support the therapeutic potential of expanding intratumoral cDC1s through local and sustained delivery of FLT3L, CXCL9, and CCL5.

immunology↗

bioRxiv2025

Small-molecule perturbation profiling reveals a mechanistic link between STING signaling and lipid metabolism in macrophages and dendritic cells

The DNA sensor cGAS and the signaling adaptor STING play a key role in the innate immune response to microbial and endogenous DNA in the cytoplasm. The cGAS-STING signaling pathway has evolved to promote immune defense and organismal fitness, yet its dysregulation can lead to chronic inflammation, autoimmunity, and neurodegeneration. Upon sensing double- stranded DNA, cGAS produces a cyclic dinucleotide second messenger that binds to STING in the endoplasmic reticulum. Ligand-bound STING translocates to the Golgi and activates the protein kinase TBK1 and the transcription factor IRF3, resulting in IRF3-driven interferon (IFN) gene transcription. This cascade of molecular events is mechanistically linked to intracellular lipid membrane dynamics and protein lipidation. To explore whether STING signaling is controlled by the availability and metabolic flux of cellular lipids, we screened small-molecule compounds targeting lipid metabolic pathways for their influence on STING agonist-responsive IFN induction. These screens identified inhibitors of the fatty acid synthase FAS and lipases as potent suppressors of STING signaling. An inhibitor of the cholesterol-esterifying enzyme SOAT1 enhanced STING-dependent IFN induction in mouse cells while attenuating it in human cells. Our findings reveal a connection between STING signaling and lipid metabolism and opportunities for expanding the toolbox for treating clinical conditions that arise from aberrant STING activity.

immunology↗

bioRxiv2025

Resolution of in situ inflammation in human lupus nephritis into principal immune cell trajectories

In human lupus nephritis (LuN), tubulointerstitial inflammation (TII) is prognostically more important than glomerular inflammation. However, a comprehensive understanding of both TII complexity and heterogeneity is lacking. Herein, we used high-dimensional confocal microscopy and specialized computer vision techniques to quantify immune cell populations and localize these within normal and diseased renal cortex structures. With these tools, we compared LuN to renal allograft rejection (RAR) and normal kidney. In both LuN and RAR, the 33 characterized immune cell populations formed discrete subgroups whose constituents co-varied in prevalence across biopsies. In both diseases, these co-variant immune cell subgroups organized into the same unique niches. Therefore, inflammation could be resolved into trajectories representing the relative prevalence and density of cardinal immune cell members of each co-variant subgroup. Indeed, in any one biopsy, the inflammatory state could be characterized by quantifying constituent immune cell trajectories. Remarkably, LuN heterogeneity could be captured by quantifying a few myeloid immune cell trajectories while RAR was more complex with additional T cell trajectories. Our studies identify rules governing renal inflammation and thus provide an approach for resolving LuN into discrete mechanistic categories. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/638655v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@109dd33org.highwire.dtl.DTLVardef@995037org.highwire.dtl.DTLVardef@161525dorg.highwire.dtl.DTLVardef@6692d8_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

immunology↗

bioRxiv2025

The types of prions and liquid-like aggregates formed by the yeast protein Rnq1 are controlled by interactions between its non-prion and prion domains

Prions are self-propagating protein conformations usually existing as amyloid aggregates. [PIN+], a prion form of the Rnq1 protein occasionally found in wild and laboratory yeast strains, facilitates both the de novo formation and destabilization of other yeast prions, and affects aggregation and toxicity of human misfolding disease proteins expressed in yeast. Rnq1 contains a short N-terminus with no confirmed function (the non-prion domain, NPD) and a C-terminus that carries four QN-rich regions and is sufficient for [PIN+] formation and maintenance (prion domain, PD). In the current study, a genetic screen identified the NPD T27P mutation that blocks transmission of the [PIN+] prion state from wild type Rnq1 (Rnq1WT) to mutant Rnq1T27P. The mutation doesnt prevent Rnq1T27P from switching to a prion state when overexpressed in vivo, or from forming amyloid fibers in vitro. Furthermore, like [PIN+WT], the newly formed [PIN+T27P]s promote the de novo appearance of the Sup35-based prion [PSI+]. We conclude that the NPD mutation creates a barrier for prion transmission from [PIN+WT] to Rnq1T27P. Because fluorescence microscopy shows that Rnq1T27P efficiently joins [PIN+WT] aggregates, the barrier is likely due to the inability of Rnq1T27P to propagate the specific [PIN+WT] conformational variant. Indeed, the analysis of [PIN+T27P]s resulting from rare transmission events from [PIN+WT] indicates that these [PIN+T27P]s must undergo conformational adaptation to yield more stable prion variants. Deletion analysis revealed that T27P constrains prion conformations through the first two QN-rich regions within the PD. The finding that Rnq1T27P-YFP readily forms non-amyloid liquid-like droplets, which Rnq1WT-YFP does not form, supports the idea that the NPD affects aggregation properties of the PD. We propose that these aggregation properties are essential for Rnq1s functions, such as controlling aggregation of other proteins. This provides new insight into the role of heterologous proteins and transmission barriers in the origins of protein misfolding diseases. Author SummaryProteins must fold into the right shapes to work properly. Sometimes they fold incorrectly and stick together, forming long fiber aggregates that damage cells. This kind of "protein misfolding" causes human diseases such as Alzheimers. Certain yeast proteins behave similarly, making them useful to study this process. We investigate a yeast protein called Rnq1, which has a region that helps it misfold into fibers. These fibers can also cause other, unrelated proteins to misfold. We found that a mutation in a different part of Rnq1-- outside the aggregation region -- reduces the ability of non-mutant Rnq1 fibers to convert mutant Rnq1 into growing fiber aggregates. We also identified which section of the aggregation region is affected by this mutation. Interestingly, although the rarely converted mutant aggregates grow poorly at first, they can eventually "adapt" into a shape that grows better. The same mutation also pushes Rnq1 to form liquid-like droplets instead of fibers. Our findings show that the non-aggregating part of Rnq1 controls how Rnq1 aggregates, and, consequently, the appearance and elimination of aggregates formed by other proteins. Our work also helps explain how barriers to misfolded protein growth can be overcome, which is relevant to understanding human protein misfolding diseases.

genetics↗

bioRxiv2025

Evaluating Genetic Regulators of MicroRNAs Using Machine Learning Models

This study explores the genetic regulators of microRNAs (miRNAs) using an ensemble of machine learning models to predict miRNA expression levels from gene expression data. Employing ridge regression, we accurately predicted the expression of 353 human miRNAs (R2 > 0.5), revealing robust miRNA-gene regulatory relationships. By analyzing the coefficients of these predictive models, we identified genetic regulators for each miRNA and highlighted the multifactorial nature of miRNA regulation. Further network analysis uncovered that miRNAs with higher predictive accuracy are more densely connected to their top predictive genes, reflecting strong regulatory control within miRNA-gene networks. To refine these insights, we filtered the gene-miRNA interaction networks to identify miRNAs specifically associated with enriched pathways, such as synaptic function and cardiovascular processes. From this pathway-centric analysis, we present a curated list of miRNAs and their genetic regulators, pinpointing their activity within distinct biological contexts. Additionally, our study provides a comprehensive set of metrics and coefficients for the genes most predictive of miRNA expression, along with a filtered subnetwork of miRNAs linked to specific pathways and phenotypes. By integrating miRNA expression predictors with network analysis and pathway enrichment, this work advances our understanding of miRNA regulatory mechanisms and their roles across distinct biological systems.

bioinformatics↗

bioRxiv2024

Assessing the helical stability of polyXYs at the boundaries of Intrinsically Disordered Regions with MD simulations

Intrinsically disordered regions (IDRs) in proteins lack stable structure. By carrying many hydrophilic and charged residues, it prevents them from forming globular domains and contributes to their flexibility and accessibility. Naturally, regions with reduced amino acid composition (low complexity regions; LCRs) occur within IDRs. Disorder and low complexity in protein sequences are linked to various biological functions including phase separation, regulation, and molecular interactions, and mutations in these regions can contribute to several diseases including cancer. Understanding these biological properties requires examination of the structural properties of IDRs and the LCRs within, but their inherently dynamic nature requires specific approaches combining sequence analyses, structure predictions and molecular dynamics (MD) simulations. Here, we leverage our previous work where we identified that some types of LCRs combining two residues (polyXY) are frequent within IDRs and confer them with propensity to form helical conformation. We identify a significant accumulation of such polyXYs at the ends of IDRs following alpha-helices that start outside the IDR and may extend through the polyXY into the IDR, particularly from the N-terminal end of the IDR. MD simulations support the dynamic nature of such helical conformations. Our results suggest a mechanism by which evolutionary emergence of LCRs at IDR ends could provide proteins with flexible regions for fold-upon-binding.

bioinformatics↗

bioRxiv2023

Aquaporin 1 confers apoptosis resistance in pulmonary arterial smooth muscle cells from the SU5416 hypoxia rat model

Pulmonary arterial hypertension (PAH) is a deadly condition that arises from increased pulmonary vascular resistance due to contraction and remodeling of the pulmonary arteries. The structural changes that occur in the pulmonary arteries include thickening of the medial (smooth muscle) layer resulting from increased proliferation and resistance to apoptosis. The mechanisms underlying apoptosis resistance in PAH are not fully understood. In cancer cells, high expression of aquaporin 1 (AQP1), a water channel, is associated with apoptosis resistance. We previously showed functional AQP1 protein was expressed in pulmonary arterial smooth muscle cells (PASMCs) and was upregulated in pre-clinical models of pulmonary hypertension. Whether AQP1 controls susceptibility of PASMCs to apoptosis in pre-clinical models of PAH is unknown. In this study, we used PASMCs isolated from control rats and rats exposed to SU5416 plus hypoxia (SuHx) to test the role of AQP1 in modulating apoptosis in PASMCs. We found that elevated levels of AQP1 in PASMCs from pulmonary hypertensive rats were necessary for resistance to apoptosis, and that apoptosis resistance could be conferred by increasing expression of AQP1 in PASMCs from control rats. Moreover, in exploring the downstream pathways involved, we found AQP1 levels influence the expression of Bcl-2, with enhanced AQP1 levels corresponding to increased Bcl-2 expression, resulting in reductions in the ratio of BAX to Bcl-2 as are typically associated with apoptosis resistance. These early results provide a mechanism by which AQP1 can regulate PASMC fate and suggest further investigation could provide additional clues regarding whether AQP1-mediated apoptosis resistance contributes to PAH development or progression and whether AQP1 might be a suitable target for therapy.

cell biology↗

bioRxiv2023

A Novel Interaction Between Aquaporin 1 and Caspase-3 in Pulmonary Arterial Smooth Muscle Cells

Pulmonary arterial hypertension (PAH) is a disease in which remodeling of the precapillary pulmonary vasculature leads to hyperplasia and hypertrophy of the muscular vascular wall, and the formation of vaso-occlusive lesions. These pathologic changes are predominantly due to abnormal proliferation and migration of pulmonary arterial smooth muscle cells (PASMCs), enhanced cellular functions that have been linked to increases in the cell membrane protein aquaporin-1 (AQP1). However, the mechanisms underlying increased AQP1 abundance have not been fully elucidated. Here we present data that establishes a novel interaction between AQP1 and the proteolytic enzyme caspase-3. In silico analysis of the AQP1 protein reveals two caspase-3 cleavage sites on its c-terminal tail, proximal to known ubiquitin sites. Using biotin proximity ligase techniques, we establish that AQP1 and caspase-3 interact in both HEK293A cells and rat PASMCs. Furthermore, we demonstrate that AQP1 levels increase and decrease with enhanced caspase-3 activity and inhibition respectively. Ultimately, further work characterizing this interaction could provide the foundation for novel PAH therapeutics.

cell biology↗

bioRxiv2023

Adaptation of the Spalax galili transcriptome to life under hypoxia may hold a key to a complex phenotype including longevity and cancer resistance

The muroid rodent Nannospalax galili (syn. Spalax) is adapted to life in underground burrows and tolerates acute exposure to severe hypoxia. Adaptation to hypoxia is correlated with delayed onset of ageing and resistance against tumour formation. Spalax becomes five to seven times older than its relatives, the mouse and rat, without displaying signs of ageing or developing ageing-related disorders like cancer. Investigating and understanding adapted genes and gene regulatory networks of Spalax might pinpoint novel strategies to maintain an extended healthy phenotype in humans. Here we analysed and compared RNA-Seq data of liver, kidney and spleen of Spalax and rat subjected to 6% O2 or normoxia. We identified differentially expressed genes and pathways common to multiple organs in Spalax and rat. Body-wide differences between Spalax and rat affected biological processes like cell death, defence against reactive oxygen species (ROS), DNA repair, energy metabolism, immune response and angiogenesis, which altogether might play a crucial role in Spalaxs adaptation to life under oxygen deprivation. In all organs, mRNA expression of genes associated with genome stability maintenance and DNA repair was elevated in Spalax compared to rat, accompanied by a lower gene expression of genes associated with aerobic energy metabolism and proinflammatory processes. These transcriptomic changes might be accountable for the extraordinary lifespan of Spalax and its cancer resistance. Our results reveal gene regulatory networks that become candidates for the investigation of the molecular bases that underlie the complex phenotype of Spalax.

evolutionary biology↗

bioRxiv2021

Characterization of USH1C/harmonin in the human retina provides insights into pathophysiology and therapy options for Usher syndrome

Usher syndrome (USH) is the most common form of hereditary deafness-blindness in humans. USH is a complex genetic disorder, assigned to three clinical subtypes differing in onset, course, and severity, with USH1 being the most severe. Rodent USH1 models do not reflect the ocular phenotype observed in human patients to date; hence, little is known about the pathophysiology of USH1 in the human eye. One of the USH1 genes, USH1C, exhibits extensive alternative splicing and encodes numerous harmonin protein isoforms that function as scaffolds for organizing the USH interactome. RNA-seq analysis of human retinas uncovered harmonin_a1 as the most abundant transcript of USH1C. Bulk RNA-seq analysis and immunoblotting showed abundant expression of harmonin in Muller glia cells (MGCs) and retinal neurons. Furthermore, harmonin was localized in the terminal endfeet and apical microvilli of MGCs, presynaptic region (pedicle) of cones, and outer segments of rods as well as at adhesive junctions of MGCs and photoreceptors in the outer limiting membrane (OLM). Our data provide evidence for the interactions of harmonin with OLM molecules in photoreceptors (PRCs) and MGCs and rhodopsin in PRCs. Subcellular expression and colocalization of harmonin correlate with the clinical phenotype observed in USH1C patients. In addition, primary cilia defects in USH1C patient-derived fibroblasts could be reverted by the delivery of harmonin_a1 transcript isoform. Our data provide novel insights into PRC cell biology, USH1C pathophysiology, and for developing gene therapy treatment.

molecular biology↗

bioRxiv2020

Reduced Suprathreshold Auditory Nerve Responses are Associated with Thinner Temporal Cortex and Slower Processing Speed in Presbycusis

Epidemiological evidence shows an association between hearing loss and dementia in elderly people. However, the mechanisms that connect hearing impairments and cognitive decline are still unknown. Here we propose that a suprathreshold auditory-nerve impairment is associated with cognitive decline and brain atrophy. Methods: audiological, neuropsychological, and brain structural 3-Tesla MRI data were obtained from elders with different levels of hearing loss recruited in the ANDES cohort. The amplitude of waves I (auditory nerve) and V (midbrain) from auditory brainstem responses were measured at 80 dB nHL. We also calculated the ratio between wave V and I as a proxy of a suprathreshold brainstem function. Results: we included a total of 101 subjects (age: 73.5 {+/-} 5.2 years (mean {+/-} SD), mean education: 9.5 {+/-} 4.2 years, and mean audiogram thresholds (0.5-4 kHz): 25.5 {+/-} 12.0 dB HL). We obtained reliable suprathreshold waves V in all subjects (n=101), while replicable waves I were obtained in 92 subjects (91.1%). Partial Spearman correlations (corrected by age, gender, education and hearing thresholds) showed that reduced suprathreshold wave I responses were associated with thinner bilateral medial and inferior temporal cortex and, with slower processing speed as evidenced by the Trail-Making Test-A and digit symbol tests. Non-significant correlations were obtained between wave I amplitudes and other cognitive domains. Conclusions: These results evidence that reduced suprathreshold auditory nerve responses in presbycusis are associated with slower processing speed and brain structural changes in the temporal cortex.

neuroscience↗

bioRxiv2019

Computational identification of cell-specific variable regions in ChIP-seq data

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is used to identify genome-wide DNA regions bound by proteins. Given one ChIP-seq experiment with replicates, binding sites not observed in all the replicates will usually be interpreted as noise and discarded. However, the recent discovery of high-occupancy target (HOT) regions suggests that there are regions where binding of multiple transcription factors can be identified. To investigate ChIP-seq variability, we developed a reproducibility score and a method that identifies cell-specific variable regions in ChIP-seq data by integrating replicated ChIP-seq experiments for multiple protein targets on a particular cell type. Using our method, we found variable regions in human cell lines K562, GM12878, HepG2, MCF-7, and in mouse embryonic stem cells (mESCs). These variable-occupancy target regions (VOTs) are CG dinucleotide rich, and show enrichment at promoters and R-loops. They overlap significantly with HOT regions, but are not blacklisted regions producing non-specific binding ChIP-seq peaks. Furthermore, in mESCs, VOTs are conserved among placental species suggesting that they could have a function important for this taxon. Our method can be useful to point to such regions along the genome in a given cell type of interest, to improve the downstream interpretative analysis before follow up experiments.

bioinformatics↗

bioRxiv2019

Coevolutive, Evolutive and Stochastic Information in Protein-Protein Interactions

Here, we investigate the contributions of coevolutive, evolutive and stochastic information in determining protein-protein interactions (PPIs) based on primary sequences of two interacting protein families A and B. Specifically, under the assumption that coevolutive information is imprinted on the interacting amino acids of two proteins in contrast to other (evolutive and stochastic) sources spread over their sequences, we dissect those contributions in terms of compensatory mutations at physically-coupled and uncoupled amino acids of A and B. We find that physically-coupled amino-acids at short range distances store the largest per-contact mutual information content, with a significant fraction of that content resulting from coevolutive sources alone. The information stored in coupled amino acids is shown further to discriminate multi-sequence alignments (MSAs) with the largest expectation fraction of PPI matches - a conclusion that holds against various definitions of intermolecular contacts and binding modes. When compared to the informational content resulting from evolution at long-range interactions, the mutual information in physically-coupled amino-acids is the strongest signal to distinguish PPIs derived from cospeciation and likely, the unique indication in case of molecular coevolution in independent genomes as the evolutive information must vanish for uncorrelated proteins.\n\nSIGNIFICANCEThe problem of predicting protein-protein interactions (PPIs) based on multi-sequence alignments (MSAs) appears not completely resolved to date. In previous studies, one or more sources of information were taken into account not clarifying the isolated contributions of coevolutive, evolutive and stochastic information in resolving the problem. By benefiting from data sets made available in the sequence- and structure-rich era, we revisit the field to show that physically-coupled amino-acids of proteins store the largest (per contact) information content to discriminate MSAs with the largest expectation fraction of PPI matches - a result that should guide new developments in the field, aiming at characterizing protein interactions in general.

biophysics↗