Biology subjects

Martin, M.

Publications and source records attributed to Martin, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Dynamic cortical behavior of plant protoplasts reveals unexpected similarities between plant and animal cells

In contrast to animal cells with their contractile cortical cytoskeleton, plant cells are encased in walls and are usually thought to behave like stiff, pressurized vessels. When digesting the cell wall, plant protoplasts form spherical shapes, further consolidating this model. Here we challenge this apparent opposition between animal and plant cells. We show that plant protoplasts can form protrusions. More precisely, using plasma membrane markers, we reveal that 27 {+/-} 1% of the protoplasts show dot-like protrusions and 16 {+/-} 7% of protoplasts show long (typically 1-20 m, up to 200 m) protrusions that we name "filopods". We demonstrate that this behavior is independent of the plant species, the membrane marker or the osmolyte. Protrusions can host large and long structures, such as microtubule bundles, which in turn can impact the mechanical behavior of the protrusions. We find that filopods can form de novo when increasing osmolarity, that they most likely move passively, and that they can attach to artificial surfaces. Altogether, these observations show that forming and retaining protrusions is not exclusive to animal cells. This calls for revisiting the dynamics and probing ability of the plant cell cortex in different osmotic and mechanical environments.

plant biology↗

bioRxiv2024

Multi-context seeds enable fast and high-accuracy read mapping

A key step in sequence similarity search is to identify shared seeds between a query and a reference sequence. A well-known tradeoff is that longer seeds offer fast searches but reduce sensitivity in variable regions. We introduce multi-context seeds (MCS), which allow to store seeds with different lengths in the same index structure, thus retaining the advantages of both short and long seeds. We demonstrate the applicability of MCS by implementing them in strobealign. Strobealign with MCS substantially improves accuracy compared to the previous version with little cost in runtime and no memory overhead.

bioinformatics↗

bioRxiv2024

Identification of potential sepsis therapeutic drugs using a zebrafish rapid screening approach

In the military, combat wound infections can progress rapidly to life-threatening sepsis. Discovery of effective small molecule drugs to prevent and/or treat sepsis is a priority. To identify potential sepsis drug candidates, we used an optimized larval zebrafish model of endotoxicity/sepsis (Philip et al., 2017) to screen commercial libraries of U.S. Food and Drug Administration (FDA)- approved drugs and other active pharmaceutical ingredients (API) known to affect pathways implicated in the initiation and progression of sepsis in humans (i.e., inflammation, mitochondrial dysfunction, coagulation, and apoptosis). We induced endotoxicity in 3- and 5-day post fertilization larval zebrafish (characterized by mortality and tail fin edema (vascular leakage)) by immersion exposure to Pseudomonas aeruginosa 60 g/mL lipopolysaccharide (LPS) for 24 hours, then screened for the rescue potential of 644 selected drugs simultaneously with LPS at 10 M. After LPS exposure, we used a neurobehavioral assay (light-dark test) to further evaluate rescue from endotoxicity and to determine possible off-target drug side effects. We identified 29 drugs with > 60% rescue of tail edema and mortality. Three drugs (Ketanserin, Tegaserod, and Brexpiprazole) produced 100% rescue and did not differ from the controls in the light-dark test, suggesting a lack of off-target neurobehavioral effects. Further testing of these three drugs at a nearly 100% lethal concentration of Klebsiella pneumoniae LPS (45 g/mL) showed 100% rescue from mortality and 88%-100% mitigation against tail edema. The success of the three identified drugs in a zebrafish endotoxicity/sepsis model warrants further evaluation in mammalian sepsis models.

pharmacology and toxicology↗

bioRxiv2024

Genomic stability in the Galapagos Scalesia adaptive radiation: Consistent transposable element accumulation despite hybridization and ecological niche shifts

Transposable elements (TEs) have been hypothesized to play a pivotal role in driving diversification by facilitating the emergence of novel phenotypes and the accumulation of divergence between species. Hybridization and adaptation to novel niches are hypothesized to influence TE accumulation in genomes by disrupting genomic regulation, including the suppression of TE replication. The rapid speciation and ecological diversification characteristic of adaptive radiations offer a unique opportunity to examine the link between TE accumulation and speciation, diversification, hybridization and adaptation. Here, focusing on all 15 species of the genus Scalesia (Asteraceae), a radiation endemic to the Galapagos Islands, we test whether hybridization or shifts in ecological niche are associated with changes in TE accumulation in genomes. Our analyses reveal little to no variation in TE accumulation among Scalesia species nor its hybrid populations. Shifts in ecological niches, linked to climatic variation, did not result in discernible changes in TE accumulation, a surprising finding given the anticipated selective pressure imposed by aridity, a factor often linked to genome size reduction. We found no distinct patterns in the temporal accumulation of TEs, and no effects at the class or superfamily level. Our findings challenge the assertion that TEs have directly driven diversification, speciation and local adaptation. Instead, we suggest that TEs may simply be along for the ride, rather than actively contributing to plant diversification.

evolutionary biology↗

bioRxiv2024

MITF Targets in Gastrointestinal Stromal Tumors: Implication in Autophagy and Extracellular Vesicle Secretion

Previous studies have identified Microphthalmia-associated Transcription Factor (MITF) involvement in regulating Gastrointestinal Stromal Tumors (GIST) growth and cell cycle progression. This study uses Chromatin Immunoprecipitation combined with high-throughput sequencing (ChIP-seq) and RNA sequencing to explore MITF-modulated genes in GIST. Our findings reveal that MITF regulates genes involved in lysosome biogenesis, vesicle generation, autophagy, and mTOR signaling pathways. Comparative transcriptome analysis following MITF silencing in GIST cells shows differential enrichment in mTOR signaling, impacting tumor growth and autophagy. In the context of cancer, the interplay between autophagy and extracellular vesicle release can influence tumor progression and metastasis. We examined MITFs role in autophagy and extracellular vesicle (EV) production in GIST, finding that MITF overexpression increases autophagy, as shown by elevated LC3II levels while silencing MITF disrupts autophagosome and autolysosome formation. Despite no significant changes in EV size or number, MITF silencing notably reduces KIT expression in EV content. KIT secretion in EVs has been linked to GIST metastasis, suggesting that MITF is a crucial target for managing tumor growth and metastasis in GIST.

cancer biology↗

bioRxiv2024

Interpretably deep learning amyloid nucleation by massive experimental quantification of random sequences

Protein aggregation is a pathological hallmark of more than fifty human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experimental datasets. Here we directly address this data shortage by experimentally quantifying the amyloid nucleation of >100,000 protein sequences. This unprecedented dataset reveals the limited performance of existing computational methods and allows us to train CANYA, a convolution-attention hybrid neural network that accurately predicts amyloid nucleation from sequence. We adapt genomic neural network interpretability analyses to reveal CANYAs decision-making process and learned grammar. Our results illustrate the power of massive experimental analysis of random sequence-spaces and provide an interpretable and robust neural network model to predict amyloid nucleation.

genomics↗

bioRxiv2024

Predicted mechanistic impacts of human protein missense variants

Genome sequencing efforts have led to the discovery of tens of millions of protein missense variants found in the human population with the majority of these having no annotated role and some likely contributing to trait variation and disease. Sequence-based artificial intelligence approaches have become highly accurate at predicting variants that are detrimental to the function of proteins but they do not inform on mechanisms of disruption. Here we combined sequence and structure-based methods to perform proteome-wide prediction of deleterious variants with information on their impact on protein stability, protein-protein interactions and small-molecule binding pockets. AlphaFold2 structures were used to predict approximately 100,000 small-molecule binding pockets and stability changes for over 200 million variants. To inform on protein-protein interfaces we used AlphaFold2 to predict structures for nearly 500,000 protein complexes. We illustrate the value of mechanism-aware variant effect predictions to study the relation between protein stability and abundance and the structural properties of interfaces underlying trans protein quantitative trait loci (pQTLs). We characterised the distribution of mechanistic impacts of protein variants found in patients and experimentally studied example disease linked variants in FGFR1.

bioinformatics↗

bioRxiv2024

A function of Spalt proteins in heterochromatin organization and maintenance of genomic DNA integrity

The phylogenetically conserved Spalt proteins regulate gene expression and participate in a variety of cell fate choices during multicellular development, generally acting as transcriptional repressors in different gene regulatory networks. Paradoxically, besides their roles as DNA sequence-specific transcription factors, Spalt proteins show a consistent localization to heterochromatic regions. They can act through interactions with the Nucleosome remodeling and deacetylase complex (NuRD) to promote closing of open chromatin domains, but their activities as epigenetic regulators also rely on interactions with DNA Methyltransferases or with the Lysine-specific histone demethylase LSD1, suggesting that they can participate in multiple regulatory mechanisms. Here we describe several major consequences of loss of spalt function in Drosophila cells, including changes in chromatin accessibility affecting mostly pericentromeric heterochromatin, the generation of DNA damage, alterations in the localization of chromosomes within the nucleus in polyploid cells of the salivary glands and miss-expression of transposable elements. We suggest that most of these effects are related to roles of Spalt proteins in the regulation of heterochromatin formation. We propose that Drosophila Spalt proteins have two complementary functions, acting as sequence-specific transcriptional repressors on specific target genes and regulating more global gene silencing through the generation or maintenance of heterochromatic domains.

developmental biology↗

bioRxiv2024

In silico modelling of CD8 T cell immune response links genetic regulation to population dynamics

The CD8 T cell immune response operates at multiple temporal and spatial scales, including all the early complex biochemical and biomechanical processes, up to long term cell population behavior. In order to model this response, we devised a multiscale agent-based approach using Simuscale software. Within each agent (cell) of our model, we introduced a gene regulatory network (GRN) based upon a piecewise deterministic Markov process (PDMP) formalism. Cell fate - differentiation, proliferation, death - was coupled to the state of the GRN through rule-based mechanisms. Cells interact in a 3D computational domain and signal to each other via cell-cell contacts, influencing the GRN behavior. Results show the ability of the model to correctly capture both population behaviour and molecular time-dependent evolution. We examined the impact of several parameters on molecular and population dynamics, and demonstrated the add-on value of using a multiscale approach by showing that a higher degradation rate for the protein controlling cell death induces a later peak in the response.

systems biology↗

bioRxiv2024

Vaginal lactobacilli produce anti-inflammatory beta-carboline compounds.

The vaginal microbiome is a lactobacilli-dominant, human-adapted community consistently found in people around the world. Presence of lactobacilli-dominant vaginal microbial communities, apart from Lactobacillus iners, is associated with reduced vaginal inflammation and reduced levels of pro-inflammatory cytokines. Loss of lactobacilli-dominance is associated with inflammatory conditions such as bacterial vaginosis. It remains unclear if health-associated lactobacilli actively promote the anti-inflammatory immune homeostasis of the vaginal mucosa and if so, by which mechanisms. We have identified that Lactobacillus crispatus, a key vaginal bacterial species, secretes a family of {beta}-carboline compounds with anti-inflammatory activity. These compounds suppress NF{kappa}B and interferon signaling downstream of multiple pattern recognition receptors in human macrophages and significantly dampen type I interferon receptor activation. Topical vaginal application of an anti-inflammatory {beta}-carboline compound, perlolyrine, was sufficient to significantly reduce vaginal inflammation in a mouse model of genital herpes infection. Together, we identify a key family of compounds by which vaginal lactobacilli mediate host immune homeostasis and could highlight a new therapeutic avenue for vaginal inflammation.

microbiology↗

bioRxiv2024

SARS-CoV-2 Omicron lineage XBB spike structures, conformations, antigenicity, and receptor recognition

A recombinant lineage of the SARS-CoV-2 Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryo-EM structures of XBB.1.5, XBB.1.16, EG.5 and EG.5.1 spike (S) ectodomains to reveal reinforced 3-RBD-down receptor inaccessible closed states mediated by interprotomer receptor binding domain (RBD) interactions previously observed in BA.1 and BA.2. Improved XBB.1.5 and XBB.1.16 RBD stability compensated for stability loss caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. S1 subunit mutations had long-range impacts on conformation and epitope presentation in the S2 subunit. Our results reveal continued S protein evolution via simultaneous optimization of multiple parameters including stability, receptor binding and immune evasion, and the dramatic effects of relatively few residue substitutions in altering the S protein conformational landscape.

biochemistry↗

bioRxiv2024

Molecular structure discovery for untargeted metabolomics using biotransformation rules and global molecular networking

Although untargeted mass spectrometry-based metabolomics is crucial for understanding lifes molecular underpinnings, its effectiveness is hampered by low annotation rates of the generated tandem mass spectra. To address this issue, we introduce a novel data-driven approach, Biotransformation-based Annotation Method (BAM), that leverages molecular structural similarities inherent in biochemical reactions. BAM operates by applying biotransformation rules to known anchor molecules, which exhibit high spectral similarity to unknown spectra, thereby hypothesizing and ranking potential structures for the corresponding suspect molecule. BAMs effectiveness is demonstrated by its success in annotating suspect spectra in a global molecular network comprising hundreds of millions of spectra. BAM was able to assign correct molecular structures to 24.2 % of examined anchor-suspect cases, thereby demonstrating remarkable advancement in metabolite annotation.

bioinformatics↗

bioRxiv2024

Identifying the function of the NMDA NR1C2 subunit through its interaction with Magi-2 during inflammatory pain

Much is understood about the structure and gating properties of NMDA receptors (NMDAR), but the function of the carboxy-terminal splice variant of the NR1 subunit, NR1C2 has never been identified. By studying the scaffolding protein Magi-2 in animal models of inflammatory pain, we discovered how NR1C2 protein is specifically regulated. We found that Magi-2 deficiency resulted in decreased pain behavior and a concomitant reduction in NR1C2 protein. Magi-2 contains WW domains, domains typically found in ubiquitin ligases. We identified an atypical WW-binding domain within NR1C2 which conferred susceptibility to Nedd4-1 ubiquitin-ligase dependent degradation. We used lipidated peptidomimetics derived from the NR1C2 sequence and found that NR1C2 protein levels and pain behavior can be pharmacologically targeted. The function of NR1C2 is to give lability to a pool of NMDAR, important for pain signaling.

neuroscience↗

bioRxiv2024

Opioid-driven disruption of the septal complex reveals a role for neurotensin- expressing neurons in withdrawal

Because opioid withdrawal is an intensely aversive experience, persons with opioid use disorder (OUD) often relapse to avoid it. The lateral septum (LS) is a forebrain structure that is important in aversion processing, and previous studies have linked the lateral septum (LS) to substance use disorders. It is unclear, however, which precise LS cell types might contribute to the maladaptive state of withdrawal. To address this, we used single-nucleus RNA-sequencing to interrogate cell type specific gene expression changes induced by chronic morphine and withdrawal. We discovered that morphine globally disrupted the transcriptional profile of LS cell types, but Neurotensin-expressing neurons (Nts; LS-Nts neurons) were selectively activated by naloxone. Using two-photon calcium imaging and ex vivo electrophysiology, we next demonstrate that LS-Nts neurons receive enhanced glutamatergic drive in morphine-dependent mice and remain hyperactivated during opioid withdrawal. Finally, we showed that activating and silencing LS-Nts neurons during opioid withdrawal regulates pain coping behaviors and sociability. Together, these results suggest that LS-Nts neurons are a key neural substrate involved in opioid withdrawal and establish the LS as a crucial regulator of adaptive behaviors, specifically pertaining to OUD.

neuroscience↗

bioRxiv2024

Rare genetic variation in Fibronectin 1 (FN1) protects against APOEe4 in Alzheimer's disease

The risk of developing Alzheimers disease (AD) significantly increases in individuals carrying the APOE{varepsilon}4 allele. Elderly cognitively healthy individuals with APOE{varepsilon}4 also exist, suggesting the presence of cellular mechanisms that counteract the pathological effects of APOE{varepsilon}4; however, these mechanisms are unknown. We hypothesized that APOE{varepsilon}4 carriers without dementia might carry genetic variations that could protect them from developing APOE{varepsilon}4-mediated AD pathology. To test this, we leveraged whole genome sequencing (WGS) data in National Institute on Aging Alzheimers Disease Family Based Study (NIA-AD FBS), Washington Heights/Inwood Columbia Aging Project (WHICAP), and Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) cohorts and identified potentially protective variants segregating exclusively among unaffected APOE{varepsilon}4 carriers. In homozygous unaffected carriers above 70 years old, we identified 510 rare coding variants. Pathway analysis of the genes harboring these variants showed significant enrichment in extracellular matrix (ECM)-related processes, suggesting protective effects of functional modifications in ECM proteins. We prioritized two genes that were highly represented in the ECM-related gene ontology terms, (FN1) and collagen type VI alpha 2 chain (COL6A2) and are known to be expressed at the blood-brain barrier (BBB), for postmortem validation and in vivo functional studies. The FN1 and COL6A2 protein levels were increased at the BBB in APOE{varepsilon}4 carriers with AD. Brain expression of cognitively unaffected homozygous APOE{varepsilon}4 carriers had significantly lower FN1 deposition and less reactive gliosis compared to homozygous APOE{varepsilon}4 carriers with AD, suggesting that FN1 might be a downstream driver of APOE{varepsilon}4-mediated AD-related pathology and cognitive decline. To validate our findings, we used zebrafish models with loss-of-function (LOF) mutations in fn1b - the ortholog for human FN1. We found that fibronectin LOF reduced gliosis, enhanced gliovascular remodeling and potentiated the microglial response, suggesting that pathological accumulation of FN1 could impair toxic protein clearance, which is ameliorated with FN1 LOF. Our study suggests vascular deposition of FN1 is related to the pathogenicity of APOE{varepsilon}4, LOF variants in FN1 may reduce APOE{varepsilon}4-related AD risk, providing novel clues to potential therapeutic interventions targeting the ECM to mitigate AD risk.

genetics↗

bioRxiv2023

Phosphorylation in the Plasmodium falciparum proteome: A meta-analysis of publicly available data sets

Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to human, of which P. falciparum is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signalling and hence, regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics datasets, to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 28,495 phosphorylated sites on P. falciparum proteins at 5% false localisation rate (FLR) and, of those, 18,100 at 1% FLR. We identified significant sequence motifs, likely indicative of different groups of kinases, responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved, and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We were also able to identify over 180,000 phosphosites within Plasmodium species beyond falciparum, based on orthologue mapping. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signalling, and thus warranting further study for their roles in host- pathogen interactions. All data has made available via UniProtKB, PRIDE and PeptideAtlas, with visualisation interfaces for exploring phosphosites in the context of other data on Plasmodium proteins. Author SummaryPlasmodium parasites continue to pose a significant global health threat, with a high proportion of the world at risk of malaria. It is imperative to gain new insights into cell signalling and regulation of biological processes in these parasites to develop effective treatments. This study focused on post- translational modifications (PTMs) of proteins, specifically phosphorylation. We conducted a meta- analysis of 11 publicly available phosphoproteomics datasets, identifying over 28,000 phosphorylated sites on P. falciparum proteins, using very rigorous statistics to avoid reporting false positives, and mapping to over 180,000 phosphorylation sites on other species of Plasmodium. The analysis revealed distinct sequence motifs associated with different groups of phosphosites (and likely indicative of different upstream kinases), and differences in the downstream pathways regulated. Conservation analysis highlighted clusters of phosphoproteins evolving at different rates within the Plasmodium genus. Notably, phosphorylation was enriched in regions of proteins lacking distinct structural elements, known as intrinsically disordered regions (IDRs), which are poorly conserved across the genus - we speculate that they are important for modulating protein interactions. The findings provide valuable insights into the molecular mechanisms of P. falciparum, with potential implications for understanding host-pathogen interactions. The comprehensive dataset generated is now publicly accessible, serving as a valuable resource for the scientific community through UniProtKB, PRIDE, and PeptideAtlas.

bioinformatics↗

bioRxiv2023

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

bioinformatics↗

bioRxiv2023

Designing efficient randstrobes for sequence similarity analyses

Substrings of length k, commonly referred to as k-mers, play a vital role in sequence analysis, reducing the search space by providing anchors between queries and references. However, k-mers are limited to exact matches between sequences. This has led to alternative constructs, such as spaced k-mers, that can match across substitutions. We recently introduced a class of new constructs, strobemers, that can match across substitutions and smaller insertions and deletions. Randstrobes, the most sensitive strobemer proposed in [18], has been incorporated into several bioinformatics applications such as read classification, short read mapping, and read overlap detection. Randstrobes are constructed by linking together k-mers in a pseudo-random fashion and depend on a hash function, a link function, and a comparator for their construction. Recently, we showed that the more random this linking appears (measured in entropy), the more efficient the seeds for sequence similarity analysis. The level of pseudo-randomness will depend on the hashing, linking, and comparison operators. However, no study has investigated the efficacy of the underlying operators to produce randstrobes. In this study, we propose several new construction methods. One of our proposed methods is based on a Binary Search Tree (BST), which lowers the time complexity and practical runtime to other methods for some parametrizations. To our knowledge, we are also the first to describe and study the types of biases that occur during construction. We designed three metrics to measure the bias. Using these new evaluation metrics, we uncovered biases and limitations in previous methods and showed that our proposed methods have favorable speed and sampling uniformity to previously proposed methods. Lastly, guided by our results, we change the seed construction in strobealign, a short-read mapper, and find that the results change substantially. Also, we suggest combining the two versions to improve accuracy for the shortest reads in our evaluated datasets. Our evaluation highlights sampling biases that can occur and provides guidance on which operators to use when implementing randstrobes.

bioinformatics↗