Biology subjects

Alvarez, M.

Publications and source records attributed to Alvarez, M..

At least 19 recordsLinked to original sources

bioRxiv2025

Staphylococcus aureus urease is controlled by a complex regulatory network and promotes dissemination during catheter-associated urinary tract infections (CAUTI)

Catheter-associated urinary tract infections (CAUTIs) are one of the most common hospital-associated infections in the United States, accounting for >1 million cases annually. One CAUTI-associated pathogen, Staphylococcus aureus, is commonly found persisting asymptomatically in the bladder of catheterized individuals, increasing these individuals risk of developing CAUTI. Importantly, S. aureus is not only associated with severe symptoms, including bacteremia and septic shock, but it also produces a common uropathogen associated virulence factor, urease. Despite its importance, urease has only been well-studied in the uropathogen Proteus mirabilis. While previous studies identified three S. aureus urease regulators, CodY, CcpA, and Agr, the environmental signals required for expression and activity, and the contribution of urease to CAUTI have not been explored. In this study, we investigate how the urease regulatory pathways coordinate expression and activity in response to environmental signals present within the catheterized urinary tract. Our findings demonstrate that stationary phase significantly induces S. aureus urease expression and activity. Additionally, we identified predicted binding sites in the urease promoter for three regulators previously implicated in urease expression - CodY, CcpA, and SigB - as well as SrrA - a previously unrecognized regulator of urease. A binding site for Agr was not present in the urease promoter. Expression and activity assays confirm the role of CodY, CcpA, SigB, SrrA, and Agr in regulating urease. Importantly, single nucleotide polymorphisms identified in the urease promoter of clinical isolates enhance urease expression. Additionally, urease promotes biofilm formation under catheterized urinary tract-like conditions in vitro and dissemination from the bladder to the kidneys at 1 day post infection in a mouse CAUTI model. Together, our data not only provide insight into the regulatory pathway controlling S. aureus urease but also emphasize the importance of studying these mechanisms in a model that mimics the host environment. AUTHOR SUMMARYCatheter-associated urinary tract infections (CAUTIs) are common hospital-associated infections and are caused by many different pathogens. Of these pathogens, Staphylococcus aureus is particularly problematic, as it often spreads to the bloodstream and results in septic shock. One of the primary virulence factors that is important for uropathogens is urease. Urease breaks down urea in urine, which results in crystalline structures that encrust urinary catheters and promote reflux to the kidney. Despite producing urease, little is known about how S. aureus regulates the enzyme. In this study, we investigate how regulatory pathways coordinate the expression and activity of urease in response to environmental signals. We show that growth during stationary phase and in conditions that mimic the urinary tract urease expression and activity are increased. We also show that five different regulators - CodY, CcpA, SigB, SrrA, and Agr control urease expression and activity. Additionally, genomic changes identified in the urease regulatory pathway of clinical urinary catheter-associated isolates enhance urease expression. Importantly, urease promotes biofilm formation and dissemination during CAUTI. Our study provides insight into the complex regulatory mechanisms controlling urease and highlights the role urease plays in the development and virulence of S. aureus CAUTI.

microbiology↗

bioRxiv2025

Determining gene specificity from multivariate single-cell RNA sequencing data

An important application of single-cell genomics experiments is to identify genes specific to biological categories or experimental conditions. Although numerous approaches have been proposed to identify such genes, we consider an axiomatic approach based on defining properties that a specificity measure should have. This leads us to develop ember (Entropy Metrics for Biological ExploRation), which we show is the only method satisfying four key desired properties for a specificity measure. Applying ember to eight tissues from eight founder mouse strains, we find that gene specificity is often unintuitive: canonical markers can be supplanted, housekeeping genes are context-dependent, and mouse strain can drive unexpected cell type switching. Unsupervised learning on entropy metrics uncovers shared genes specialized to male gonads and kidney, as well as genes specific to non-consecutive developmental stages in the kidney. To facilitate further exploration of gene specificity in mice, we have also developed a comprehensive specificity database, along with a web interface, API and MCP server. Extending ember to a human PBMC dataset collected from 255 diverse individuals, we find that variation in PBMCs is largely localized to classical monocytes. We also find genes with unique specificity by sex, age and ancestral background. Together, these applications establish ember as a powerful tool and provide a roadmap for elucidating the impact of human genetic variation using the murine model.

bioinformatics↗

bioRxiv2025

Low-temperature integration of printed electrochemical sensors into OSTE+ micrfluidics for oxygen monitoring and sensing

Real-time monitoring of biological events is essential for advancing in drug testing, disease modeling, and precision medicine. However, conventional analytical methods often lack the spatiotemporal resolution to capture dynamic cellular responses, particularly in Organ-on-a-Chip (OoC) platforms and microphysiological systems (MPS). While progress has been made in sensor development, integrating sensors into microfluidic devices remains technically challenging. Materials commonly used in microfluidics, such as polydimethylsiloxane (PDMS), are poorly suited for stable sensor integration due to low metal adhesion. Off-stoichiometry thiol-ene-epoxy (OSTE+) polymers present a promising alternative due to the presence of unreacted thiol groups. These groups enable dual functionalities: strong metal affinity for direct for robust sensor integration, and oxygen scavenging essential for microscale oxygen level control. However, their compatibility with conventional sensor fabrication methods, particularly those requiring elevated temperatures, is limited. This work introduces a low-temperature fabrication method based on inkjet printing and photonic curing, suitable for thermally sensitive substrates. Gold and silver nanoparticle inks were directly sintered onto OSTE+ using photonic curing, producing functional electrochemical sensors for spatially resolved and real-time oxygen detection. Unlike conventional thermal sintering, which is incompatible with many microfluidic materials, photonic curing preserves the chemical reactivity and mechanical properties of the polymer without requiring surface treatment or adhesive layers. To demonstrate functionality, sensors were integrated into microfluidic devices for continuous monitoring of dissolved oxygen. Real-time oxygen depletion driven by the materials intrinsic scavenging capability was successfully quantified. These findings support the compatibility of sensor integration into OSTE+ polymers enhancing the real-time monitoring capabilities in OoC and MPS systems. HighlightsO_LIInkjet-printed sensors are integrated into OSTE+ using a low-temperature protocol. C_LIO_LIPhotonic curing enables sintering of gold and silver nanoparticle inks without damaging the polymer substrate. C_LIO_LIOxygen scavenging is monitored in real time using integrated electrochemical sensors. C_LIO_LITunable oxygen gradients are achieved in OSTE+ microfluidics for organ-on-chip models. C_LI

bioengineering↗

bioRxiv2025

Inhibition of 3-mercaptopyruvate sulfurtransferase enhances CD8⁺ T-cell antitumor immunity

Hydrogen sulfide (H2S) is a redox-active gasotransmitter implicated in tumor progression and immune regulation. The enzyme 3-mercaptopyruvate sulfurtransferase (3-MST) is a key contributor to endogenous H2S and polysulfide production, but its role in tumor-immune interactions remains poorly defined. Here, we show that 3-MST is the most abundantly expressed H2S-synthesizing enzyme in human renal cell carcinoma cells (RCC) and that high 3-MST expression correlates with reduced patient survival. Pharmacological inhibition of 3-MST lowered intracellular H2S levels in Renca renal carcinoma cells, suppressed proliferation, induced apoptosis, and increased surface expression of the immunogenic markers CD70, CD86, and PD-L1. In immune cells, partial inhibition of 3-MST promoted T cell activation, as evidenced by increased CD69 expression on both CD4 helper and CD8 cytotoxic T cells. In contrast, complete inhibition of 3-MST, achieved by high concentrations of the inhibitor, modestly reduced CD8 T cell proliferation. Functionally, 3-MST inhibition potentiated antigen-specific CD8 T cell-mediated killing of tumor cells, an effect further amplified by PD-L1 blockade. These results establish 3-MST as a redox-sensitive metabolic driver of tumor growth and immune evasion in RCC and demonstrate that its inhibition can boost antitumor immune responses, offering a potential avenue for combination immunotherapy.

pharmacology and toxicology↗

bioRxiv2025

Integrated ambient modeling and genetic demultiplexing of single-cell RNA+ATAC multiome experiments with Ambimux

Single cell technologies have advanced at a rapid pace, providing assays for various molecular phenotypes. Droplet-based single cell technologies, particularly those based on nuclei isolation, such as simultaneous RNA+ATAC single-cell multiome, are susceptible to exogenous ambient molecule contamination, which can increase noise in cell type-level associations. We reasoned that genotype-based sample multiplexing can provide an opportunity to infer this ambient contamination by leveraging DNA variation in sequenced reads. Thus, we developed ambimux, a likelihood-based method to estimate ambient fractions and demultiplex single-cell multiome experiments using genotype-level data. Ambimux models the ambient or nuclear probability at the read level and thus can classify empty droplets and estimate droplet-specific ambient molecule fractions in each modality. We first evaluated our method using simulated data sets across a range of parameters. We found that ambimux closely estimated the ground truth droplet contamination fractions in the RNA (MAE=0.048) and ATAC (MAE=0.042) modalities. As a result, ambimux maintained high specificity (>95%) and was able to correctly assign singlets at considerably high ambient fractions (up to 60%) for both RNA and ATAC modalities. In comparison with models that do not consider ambient contamination, these only maintained similar sensitivity levels at considerably lower ambient fractions (up to 25%). We then generated a real data set of seven visceral adipose tissue biopsies run on a single 10x Multiome channel. We ran ambimux and detected 4,986 singlets, capturing similar numbers as other methods. Then, we sought to evaluate the fidelity of the ambient fraction estimates from ambimux. We split singlets into ambient-enriched (>5% contamination in both modalities) or nuclear-enriched (<5% in both) droplets and performed gene-peak linkage analysis. Low ambient droplets resulted in more significant hits with gene-peak links enriched at the transcription start site relative to high ambient droplets, suggesting that the ambient droplets identified by ambimux hamper the identification of biologically meaningful signals. In summary, we developed a joint single-cell multiome demultiplexing method, ambimux, that accurately models and estimates ambient molecule contamination in each modality.

bioinformatics↗

bioRxiv2025

Depletion of a neural cell adhesion molecule disrupts both epithelial and germ layer identity in sea anemone embryos

Assembly of cells into epithelial layers marks the early steps of tissue organization and embryonic development in most animals. Although several conserved proteins are known to be essential for epithelialization in bilaterians, it is unclear whether these are sufficient to drive epithelial organization in all metazoans. Using proteomics and knockdown approaches in embryos of the early-branching sea anemone Nematostella vectensis, we identified the neural cell adhesion molecule NCAM2 to be essential for organization of the primary epithelial layer. NCAM2 belongs to the immunoglobulin family of cell adhesion molecules with roles in inter-cellular adhesion and signaling. In this work, we show that NCAM2 is enriched at the apical cell junctions and is required for Nematostella epithelial cell identity. Importantly, embryos depleted for NCAM2 fail to gastrulate. Both whole-embryo germ layer patterning and tissue changes required for gastrulation are impaired. Together, our data show that in Nematostella NCAM2 is required for both epithelial and germ layer organization.

developmental biology↗

bioRxiv2025

Relevance of Nonlinear Dimensionality Reduction for Efficient and Robust Spike Sorting

Spike sorting is one of the cornerstones of extracellular electrophysiology. By leveraging advanced signal processing and data analysis techniques, spike sorting makes it possible to detect, isolate, and map single neuron spiking activity from both in vivo and in vitro extracellular electrophysiological recordings. A crucial step of any spike sorting pipeline is to reduce the dimensionality of the recorded spike waveform data. Reducing the dimensionality of the processed data is a near-universal practice, fundamentally motivated by the use of clustering algorithms responsible to detect, isolate, and sort the recorded putative neurons. In this paper we propose and illustrate on both synthetic and experimental data that employing the nonlinear dimensionality reduction technique Uniform Manifold Approximation and Projection (UMAP) can drastically improve the performance, efficiency, robustness, and scalability of spike sorting pipelines without increasing their computational cost. We show how replacing the linear or ad hoc, expert-defined, supervised nonlinear dimensionality reduction methods commonly used in spike sorting pipelines by the unsupervised, mathematically grounded, nonlinear dimensionality reduction method provided by UMAP drastically increases the number of correctly sorted neurons, makes the identification of quieter, seldom spiking neurons more reliable, enables deeper and more precise explorations and analysis of the neural code, and paves new ways toward more efficient and end-to-end automatable spike sorting pipelines of large-scale extracellular neural recording as those produced by high-density multielectrode arrays.

neuroscience↗

bioRxiv2025

The impact of ambient contamination on demultiplexing methods for single-nucleus multiome experiments

Sample multiplexing has become an increasingly common design choice in droplet-based single-nucleus multi-omic sequencing experiments to reduce costs and remove technical variation. Genotype-based demultiplexing is one popular class of methods that was originally developed for single-cell RNA-seq, but has not been rigorously benchmarked in other assays, such as snATAC-seq and joint snRNA/snATAC assays, especially in the context of variable ambient RNA/DNA contamination. To address this, we develop ambisim, a genotype-aware read-level simulator that can flexibly control ambient molecule proportions and generate realistic joint snRNA/snATAC data. We use ambisim to evaluate demultiplexing methods across several important parameters: doublet rate, number of multiplexed donors, and coverage levels. Our simulations reveal that methods are variably impacted by ambient contamination in both modalities. We then applied the demultiplexing methods to two joint snRNA/snATAC datasets and found highly variable concordance between methods in both modalities. Finally, we develop a new metric, variant consistency, which we show is correlated with cell-level ambient molecule fractions in singlets. Applying our metric to two multiplexed joint snRNA/snATAC datasets reveals variable ambient contamination across experiments and modalities. We conclude that improved modelling of ambient material in demultiplexing algorithms will increase both sensitivity and specificity.

bioinformatics↗

bioRxiv2024

Multi-Stable Bimodal Perceptual Coding within the Ventral Premotor Cortex

Neurons in the primate ventral premotor cortex (VPC) respond to both tactile and acoustic stimuli, yet how they integrate and process information from these sensory modalities remains unclear. To investigate this, we recorded VPC neuronal activity in two trained monkeys performing a bimodal detection task (BDT), in which they reported the presence or absence of either a tactile or an acoustic stimulus. Single-cell analyses revealed diverse response types, including purely tactile, purely acoustic, bimodal, and neurons with sustained activity during the decision maintenance delay--the period between stimulus offset and motor response. To further examine VPCs role in the BDT, we applied dimensionality reduction techniques to uncover low-dimensional latent dynamics in the neuronal population and conducted parallel analyses using a recurrent neural network (RNN) model trained on the same task. Neural trajectories for tactile and acoustic responses diverged sharply, whereas in stimulus-absent trials, the dynamics remained at rest. During the delay period, the trajectories exhibited a pronounced rotational dynamic, shifting toward a subspace orthogonal to the sensory response space, suggesting memory maintenance through stable equilibria. This indicates that network dynamics can sustain distinct stable states corresponding to the three potential task outcomes. Using low-dimensional modeling, we propose a universal dynamical mechanism that underlies the transition from sensory processing to memory retention, aligning with both experimental and computational findings. These results demonstrate that VPC neurons encode bimodal information, integrate competing sensory inputs, and maintain decisions across the delay period, regardless of sensory modality.

neuroscience↗

bioRxiv2024

Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue

Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.

genomics↗

bioRxiv2024

Contextual Neural Dynamics During Time Perception in Primate Ventral Premotor Cortex

Understanding how time perception adapts to cognitive demands remains a significant challenge. In some contexts, the brain encodes time categorically (as "long" or "short"), while in others, it encodes precise time intervals on a continuous scale. Although the ventral premotor cortex (VPC) is known for its role in complex temporal processes, such as speech, its specific involvement in time estimation remains underexplored. In this study, we investigated how the VPC processes temporal information during a time interval comparison task (TICT) and a time interval categorization task (TCT) in primates. We found a notable heterogeneity in neuronal responses associated with time perception across both tasks. While most neurons responded during time interval presentation, a smaller subset retained this information during the working memory periods. Population-level analysis revealed distinct dynamics between tasks: in TICT, population activity exhibited a linear and parametric relationship with interval duration, whereas in TCT, neuronal activity diverged into two distinct dynamics corresponding to the interval categories. During delay periods, these categorical or parametric representations remained consistent within each task context. This contextual shift underscores the VPCs adaptive role in interval estimation and highlights how temporal representations are modulated by cognitive demands. Significance StatementThe neural representation of time has long intrigued neuroscientists, particularly how it adapts to cognitive demands. Depending on the task, the brain encodes time either categorically ("long" or "short") or as precise intervals. While the ventral premotor cortex (VPC) is known for its role in temporal processes, its role in time estimation remains underexplored. Here, we examined how the VPC processes temporal information in primates during a time interval comparison task (TICT) and a categorization task (TCT). The VPC exhibited heterogeneous neuronal responses with distinct dynamics: a linear, parametric relationship in TICT and bifurcated dynamics in TCT. These representations remained consistent during delay periods, underscoring the VPCs adaptive role in time interval estimation.

neuroscience↗

bioRxiv2024

Interplay of EGFR, JNK and ROS signalling in soma-germline communication in the Drosophila testis

Cell communication via signalling exchange plays a pivotal role in multicellular development for building functional tissues and organs. In the Drosophila testis, a pair of somatic cyst cells (CCs) encapsulate the germline that differentiates through close-range EGFR signalling activation. The conserved Dlg/Scrib/Lgl cortical polarity complex and clathrin-mediated endocytosis attenuate EGFR signalling in CCs and loss of their function leads to EGFR overactivation and non-autonomous death of the neighbouring germ cells. Here we show that EGFR overactivation results in upregulation of JNK and p38 signalling in CCs and ROS levels in the germ cells that are destined to die. Our data uncover a bidirectional feedback between JNK signalling and ROS who regulate each other within the CC-germline microenvironment, while reducing the levels of either JNK or ROS restores germ cell survival. This study provides a framework of how polarity and cellular trafficking regulate the output of multiple signalling responses cell-intrinsically and in adjacent cells, to coordinate tissue-specific responses and maintain homeostasis.

cell biology↗

bioRxiv2023

PAH DEFICIENT PATHOLOGY IN HUMANIZED c.1066-11G>A PHENYLKETONURIA MICE

We have generated using CRISPR/Cas9 technology a partially humanized mouse model of the neurometabolic disease phenylketonuria (PKU), carrying the highly prevalent PAH variant c.1066-11G>A. This variant creates an alternative 3 splice site, leading to the inclusion of 9 nucleotides coding for 3 extra amino acids between Q355 and Y356 of the protein. Homozygous Pah c.1066-11A mice, with a partially humanized intron 10 sequence with the variant, accurately recapitulate the splicing defect and present almost undetectable hepatic PAH activity. They exhibit fur hypopigmentation, lower brain and body weight and reduced survival. Blood and brain phenylalanine levels are elevated, along with decreased tyrosine, tryptophan and monoamine neurotransmitter levels. They present behavioral deficits, mainly hypoactivity and diminished social interaction, locomotor deficiencies and an abnormal hind-limb clasping reflex. Changes in the morphology of glial cells, increased GFAP and Iba1 staining signals and decreased myelinization are observed. Hepatic tissue exhibits nearly absent PAH protein, reduced levels of chaperones DNAJC12 and HSP70 and increased autophagy markers LAMP1 and LC3BII, suggesting possible coaggregation of mutant PAH with chaperones and subsequent autophagy processing. This PKU mouse model with a prevalent human variant represents a useful tool for pathophysiology research and for novel therapies development.

pathology↗

bioRxiv2023

Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium

Drug Mechanism of Action (MoA) is often represented as a small repertoire of tissue-independent, high-affinity binding targets. Yet drug activity and polypharmacology are also manifested through a broad range of off-target and tissue-specific effector proteins. To address this dichotomy, we generated a compendium of drug perturbation profiles for >700 oncology drugs in cell lines representing high-fidelity models of 23 aggressive tumor subtypes, as well as an integrative framework for the proteome-wide assessment of drug-mediated, tissue-specific differential protein activity. Extending MoA and polypharmacology assessment via proteome-wide, multi-tissue analyses revealed novel polypharmacology, including for MAPK, PI3K, and folate pathways inhibitors--as supported by Western blots, thermal shift assays, and structural analysis--as well as functional inhibitors of challenging oncoprotein targets, including MYC, CTNNB1, CENPF and UHRF1. The dataset and associated computational framework might be extensible to additional compound libraries, supporting global, quantitative approaches to defining the mechanisms of action of many drugs.

systems biology↗

bioRxiv2023

Orthogonality of sensory and contextual categorical dynamics embedded in a continuum of responses from the second somatosensory cortex

How does the brain simultaneously process signals that bring complementary information, like raw sensory signals and their transformed counterparts, without any disruptive interference? Contemporary research underscores the brain ss adeptness in using decorrelated responses to reduce such interference. Both neurophysiological findings and artificial neural networks (ANNs) support the notion of orthogonal representation for signal differentiation and parallel processing. Yet, where, and how raw sensory signals are transformed into more abstract representations remains unclear. Using a temporal pattern discrimination task (TPDT) in trained monkeys, we revealed that the second somatosensory cortex (S2) efficiently segregates faithful and transformed neural responses into orthogonal subspaces. Importantly, S2 population encoding for transformed signals, but not for faithful ones, disappeared during a non-demanding version of the task, which suggests that signal transformation and their decoding from downstream areas are only active on-demand. A mechanistic computation model points to gain modulation as a possible biological mechanism for the observed context-dependent computation. Furthermore, individual neural activities that underlie the orthogonal population representations exhibited a continuum of responses, with no well-determined clusters. These findings advocate that the brain, while employing a continuum of heterogeneous neural responses, splits population signals into orthogonal subspaces in a context-dependent fashion to enhance robustness, performance, and improve coding efficiency. SIGNIFICANCE STATEMENTAn important function of the brain is turning sensation into perception. Yet, how this function is implemented remains unknown. Current research, insights from artificial neural networks, highlights using of orthogonal representations as an effective means to transform sensory signals into perceptual signals while separating and simultaneously processing the two information streams. Neuronal recordings in S2 while trained monkeys performed the TPDT, revealed that this function is implemented at the population level. While S2 encodes sensory information independently of context, the encoding of categorical information, like task parameters, is only performed when the task demands it. Such distinct and flexible organization, enriched by a spectrum of neural activities, reflects the brains efficiency, resilience, and overall purpose for solving cognitive tasks.

neuroscience↗

bioRxiv2022

Prevalence, causes and impact of TP53-loss phenocopying events in human tumors

TP53 is a master tumor suppressor gene, mutated in approximately half of all human cancers. Given the many regulatory roles of the corresponding p53 protein, it is possible to infer loss of p53 activity -- which may occur from trans-acting alterations -- from gene expression patterns. We apply this approach to transcriptomes of ~8,000 tumors and ~1,000 cell lines, estimating that 12% and 8% of tumors and cancer cell lines phenocopy TP53 loss: they are likely deficient in the activity of the p53 pathway, while not bearing obvious TP53 inactivating mutations. While some of these are explained by amplifications in the known phenocopying genes MDM2, MDM4 and PPM1D, others are not. An analysis of cancer genomic scores jointly with CRISPR/RNAi genetic screening data identified an additional TP53-loss phenocopying gene, USP28. Deletions in USP28 are associated with a TP53 functional impairment in 2.9-7.6% of breast, bladder, lung, liver and stomach tumors, and are comparable to MDM4 amplifications in terms of effect size. Additionally, in the known CNA segments harboring MDM2, we identify an additional co-amplified gene (CNOT2) that may cooperatively boost the TP53 functional inactivation effect. An analysis using the phenocopy scores suggests that TP53 (in)activity commonly modulates associations between anticancer drug effects and relevant genetic markers, such as PIK3CA and PTEN mutations, and should thus be considered as a relevant interacting factor in personalized medicine studies. As a resource, we provide the drug-marker associations that differ depending on TP53 functional status.

genomics↗

bioRxiv2022

Thalamocortical interactions shape hierarchical neural variability during stimulus perception

The brain is hierarchically organized to process sensory signals. But, to what extent do functional connections within and across areas shape this hierarchical order? We addressed this problem in the thalamocortical network, while monkeys judged the presence or absence of a vibrotactile stimulus. We quantified the variability by means of intrinsic timescales and Fano factor, and functional connectivity by means of a directionality measure in simultaneously recorded neurons sharing the same cutaneous receptive field from the somatosensory thalamus (VPL) and areas 3b and 1 from the somatosensory cortex. During the pre-stimulus periods, VPL and area 3b exhibited similarly fast dynamics while area 1 showed much slower timescales. Furthermore, during the stimulus presence, the Fano factor increased along the network VPL-3b-1. In parallel, VPL established two separate main feedforward pathways with areas 3b and 1 to process stimulus information. While feedforward interactions from VPL and area 3b were favored by neurons within specific Fano factor ranges, neural variability in area 1 was invariant to the incoming pathways. In contrast to VPL and area 3b, during the stimulus arrival, area 1 showed significant intra-area interactions, which mainly pointed to neurons with slow intrinsic timescales. Overall, our results suggest that the lower variability of VPL and area 3b regulates feedforward thalamocortical communication, while the higher variability of area 1 supports intra-cortical interactions during sensory processing. These results provide evidence of a hierarchical order along the thalamocortical network.

neuroscience↗

bioRxiv2022

An abstract categorical decision code in dorsal premotor cortex

The dorsal premotor cortex (DPC) has classically been associated with a role in preparing and executing the physical motor variables during cognitive tasks. While recent work has provided nuanced insights into this role, here we propose that DPC also participates more actively in decision-making. We recorded neuronal activity in DPC while two trained monkeys performed a vibrotactile categorization task, utilizing two distinct ranges of stimuli values that varied on two physical attributes: vibrotactile frequency and amplitude. We observed a broad heterogeneity across DPC neurons, the majority of which maintained the same response patterns across attributes and ranges, coding in the same periods, mixing temporal and categorical dynamics. The predominant categorical signal was maintained throughout the delay, movement periods and notably during the inter-trial period. Putting the entire populations data through two dimensionality reduction techniques, we found that imposing the sensory structure yielded pure categorical and temporal representations. Furthermore, projecting the activity of one population over the population axes of the other yielded identical categorical and temporal responses. Finally, we sought to identify functional subpopulations based on the combined activity of all stimuli, neurons, and time points, however we found a continuum of single-unit responses mixing temporal and categorical dynamics. All this points to DPC playing a more decision-related role than previously anticipated. SIGNIFICANCE STATEMENTThe DPCs role in the somatosensory processing network has been generally limited to movement, but our current results suggest a more abstract function. We recorded DPCs activity in two monkeys trained in a vibrotactile categorization task of two distinct physical attributes, and found a strong decision signal throughout the population, underpinned by purely temporal signals. Importantly, this abstract decision signal remains during the inter-trial period suggesting a consolidation role. Neurons maintained consistent and significant responses for both attributes, and the entire population activity converged to identical categorical representations, even when cross-projected between two contexts. These results suggest that DPC plays a larger role during decision-making and consolidation, regardless of the stimulus attributes that triggered the decision report.

neuroscience↗