Biology subjects

Serrano, L.

Publications and source records attributed to Serrano, L..

32 records · Page 2Linked to original sources

bioRxiv2021

robustica: customizable robust independent component analysis

BackgroundIndependent Component Analysis (ICA) allows the dissection of omic datasets into modules that help to interpret global molecular signatures. The inherent randomness of this algorithm can be overcome by clustering many iterations of ICA together to obtain robust components. Existing algorithms for robust ICA are dependent on the choice of clustering method and on computing a potentially biased and large Pearson distance matrix. ResultsWe present robustica, a Python-based package to compute robust independent components with a fully customizable clustering algorithm and distance metric. Here, we exploited its customizability to revisit and optimize robust ICA systematically. From the 6 popular clustering algorithms considered, DBSCAN performed the best at clustering independent components across ICA iterations. After confirming the bias introduced with Pearson distances, we created a subroutine that infers and corrects the components signs across ICA iterations to enable using Euclidean distance. Our subroutine effectively corrected the bias while simultaneously increasing the precision, robustness, and memory efficiency of the algorithm. Finally, we show the applicability of robustica by dissecting over 500 tumor samples from low-grade glioma (LGG) patients, where we define a new gene expression module with the key modulators of tumor aggressiveness downregulated upon IDH1 mutation. Conclusionrobustica brings precise, efficient, and customizable robust ICA into the Python toolbox. Through its customizability, we explored how different clustering algorithms and distance metrics can further optimize robust ICA. Then, we showcased how robustica can be used to discover gene modules associated with combinations of features of biological interest. Taken together, given the broad applicability of ICA for omic data analysis, we envision robustica will facilitate the seamless computation and integration of robust independent components in large pipelines. Contactmiquel.anglada@crg.eu

systems biology↗

bioRxiv2021

Specialization of the photoreceptor transcriptome by Srrm3-dependent microexons is required for outer segment maintenance and vision

Retinal photoreceptors differ in their transcriptomic profiles from other neuronal subtypes, likely as a reflection of their unique cellular morphology and function in the detection of light thorough the ciliary outer segment. We discovered a new layer of this molecular specialization by revealing that the vertebrate retina expresses the largest number of tissue-enriched microexons of all tissue types. A subset of these microexons is included exclusively in photoreceptor transcripts, particularly in genes involved in cilia biogenesis and in vesicle-mediated transport. This microexon program is regulated by Srrm3, a paralog of the neural microexon regulator Srrm4. Despite both proteins positively regulate retina microexons in vitro, only Srrm3 is highly expressed in mature photoreceptors and its deletion in zebrafish results in widespread downregulation of microexon inclusion, severe photoreceptor alterations and blindness. These results shed light into photoreceptors transcriptomic specialization and functionality, uncovering new cell type-specific roles for Srrm3 and microexons with implication for retinal diseases.

systems biology↗

bioRxiv2021

pyFoldX: enabling biomolecular analysis and engineering along structural ensembles

Recent years have seen an increase in the number of structures available, not only for new proteins but also for the same protein crystallized with different molecules and proteins. While protein design software have proven to be successful in designing and modifying proteins, they can also be overly sensitive to small conformational differences between structures of the same protein. To cope with this, we introduce here pyFoldX, a python library that allows the integrative analysis of structures of the same protein using FoldX, an established forcefield and modeling software. The library offers new functionalities for handling different structures of the same protein, an improved molecular parametrization module, and an easy integration with the data analysis ecosystem of the python programming language. Availability and implementationpyFoldX is an open-source library that uses the FoldX software for energy calculations and modelling. The latter can be downloaded upon registration in http://foldxsuite.crg.eu/ and is free of charge for academics. Full details on installation, tutorials covering the library functionality, and the scripts used to generate the data and figures presented in this paper are available at https://github.com/leandroradusky/pyFoldX.

bioinformatics↗

bioRxiv2020

LoxTnSeq: Transposon mutagenesis coupled with ultra-sequencing to study large random genome reductions

The Cre-Lox system is a highly versatile and powerful DNA recombinase mechanism, mainly used in genetic engineering to insert or remove desired DNA sequences. It is widely utilised across multiple fields of biology, with applications ranging from plants, to mammals, to microbes. A key feature of this system is its ability to allow recombination between mutant lox sites, traditionally named lox66 and lox71, to create a functionally inactive double mutant lox72 site. However, a large portion of the published literature has incorrectly annotated these mutant lox sites, which in turn can lead to difficulties in replication of methods, design of proper vectors, and confusion over the proper nomenclature. Here, we demonstrate common errors in annotations, the impacts they can have on experimental viability, and a standardised naming convention. We also show an example of how this incorrect annotation can induce toxic effects in bacteria that lack optimal DNA repair systems, exemplified by Mycoplasma pneumoniae. Data SummaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

synthetic biology↗

bioRxiv2020

Lox'd in translation: Contradictions in the nomenclature surrounding common lox site mutants and their implications in experiments

The removal of unwanted genetic material is a key aspect in many synthetic biology efforts, and often requires preliminary knowledge of which genomic regions are dispensable. Typically, these efforts are guided by transposon mutagenesis studies, coupled to deep-sequencing (TnSeq) to identify insertion points and gene essentiality. However, epistatic interactions can cause unforeseen changes in essentiality after the deletion of a gene, leading to the redundancy of these essentiality maps. Here, we present LoxTnSeq, a new methodology to generate and catalogue libraries of genome reduction mutants. LoxTnSeq combines random integration of lox sites by transposon mutagenesis, and the generation of mutants via cre recombinase, catalogued via deep-sequencing. When LoxTnSeq was applied to the naturally genome reduced bacterium Mycoplasma pneumoniae, we obtained a mutant pool containing 285 unique deletions. These deletions spanned from >50 bp to 28 Kb, which represent 21% of the total genome. LoxTnSeq also highlighted large regions of non-essential genes that could be removed simultaneously, and other non-essential regions that could not, providing a guide for future genome reductions.

bioengineering↗

bioRxiv2020

Translational adaptation of human viruses to the tissues they infect

Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of over 500 human-infecting viruses and determine that tropism explains changes in codon usage. Using an in silico model of translational efficiency, we validate the correspondence of the viral codon usage with the translational machinery of their tropism. In particular, we propose that the improved translational adaptation to the upper respiratory airways of the pandemic agent SARS-CoV-2 coronavirus could enhance its transmissibility. Furthermore, this correspondence is specifically defined in early viral proteins, as upon infection cells undergo reprogramming of tRNA pools that favors the translation of late counterparts.

systems biology↗

bioRxiv2020

Hypersilencing of SRRM4 suppresses basal microexon inclusion and promotes tumor growth across cancers

RNA splicing is widely dysregulated in cancer, frequently due to altered expression or activity of splicing factors. Microexons are extremely small exons (3-27 nucleotides long) that are highly evolutionarily conserved and play critical roles in promoting neuronal differentiation and development. Inclusion of microexons in mRNA transcripts is mediated by the splicing factor SRRM4, whose expression is largely restricted to neural tissues. However, microexons have been largely overlooked in prior analyses of splicing in cancer, as their small size necessitates specialized computational approaches for their detection. Here we demonstrate that despite having low expression in normal non-neural tissues, SRRM4 is hypersilenced in tumors, resulting in the suppression of basal microexon inclusion. Remarkably, SRRM4 is the most consistently silenced splicing factor across all tumor types analyzed, implying a general advantage of microexon downregulation in cancer independent of its tissue of origin. We show that this silencing is favorable for tumor growth, as decreased SRRM4 expression in tumors is correlated with an increase in mitotic gene expression, and upregulation of SRRM4 in cancer cell lines dose-dependently inhibits proliferation in vitro and in a mouse xenograft model. Further, this proliferation inhibition is accompanied by induction of neural-like expression and splicing patterns in cancer cells, suggesting that SRRM4 expression shifts the cell state away from proliferation and towards differentiation. We therefore conclude that SRRM4 acts as a proliferation brake, and tumors gain a selective advantage by cutting off this brake. SignificanceMicroexons are extremely small exons enriched in the brain that play important roles in neural development. Their inclusion is mediated by the splicing factor SRRM4, also predominantly expressed in the brain. Surprisingly, we find that low expression of SRRM4 outside of the brain is further decreased in tumors, and in fact SRRM4 is the most consistently silenced splicing factor in tumors across tissue types. We demonstrate that SRRM4 inhibits cancer cell proliferation in vitro and in vivo by inducing a neuronal differentiation program. Our findings add a new element to the overall picture of splicing dysregulation in cancer, reveal an antiproliferative function for SRRM4 and microexons outside of the brain, and may present a common therapeutic intervention point across cancer types.

cancer biology↗

bioRxiv2020

Comparative Gene Essentiality across the Bacterial Domain

Comparative genomics among bacteria has been used to gain insight into the minimal number of conserved genes in biological pathways. Essentiality studies have provided information regarding which genes are non-dispensable (essential, E) for cell growth. Here, we integrated studies of gene conservation, essentiality and function, performed in 47 diverse bacterial species. We showed there is a modest positive correlation between genome size and number of essential genes. Interestingly, we observed a clear shift in the functions assigned to these essential genes as genome size increases. For instance, essential genes related to transcription and translation dominate small genomes. In contrast, in large genomes functions of essential genes are related with cellular processing and metabolism. Finally, and most intriguing, we found a group of genes that while being highly conserved are also typically non-essential. This suggests that some housekeeping genes confer a significant survival benefit in nature while being non-essential in vitro.

genomics↗

bioRxiv2019

Model-driven design allows growth of Mycoplasma pneumoniae on serum-free media

Mycoplasma pneumoniae is a slow-growing, human pathogen that causes atypical pneumonia. Because it lacks a cell wall, many antibiotics are ineffective, and vaccination is required. Due to its reduced genome and dearth of many biosynthetic pathways, this fastidious bacterium depends on rich, undefined medium for growth, which makes large-scale cultivation for vaccine production challenging and expensive. To understand factors limiting growth, we developed a genome-scale, constraint-based model of M. pneumoniae called iEG158_mpn to describe the metabolic potential of this bacterium. We have put special emphasis on cell membrane formation to identify key lipid components to maximize bacterial growth. We have used this knowledge to predict and validate in vitro two serum-free media able to sustain growth. Our findings also show that glycolysis and lipid metabolism are much less efficient under hypoxia; these findings suggest that factors other than metabolism and membrane formation alone affect the growth of M. pneumoniae. Altogether, our modelling approach enabled us to optimize medium composition, capacitated growth in defined media and streamlined operational requirements, thereby providing the basis for stable, reproducible and less expensive vaccine production.

systems biology↗

bioRxiv2019

Translational efficiency across healthy and tumor tissues is proliferation-related

BackgroundDifferent tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon-anticodon co-adaptation in humans is not completely understood, as well as its effect on tissue-specific protein levels.\n\nResultsWe first validated the accuracy of small RNA-seq for tRNA quantification across five human cell lines. We then analyzed tRNA expression in more than 8000 tumor samples from TCGA, together with their paired mRNA-seq and proteomics data, to determine the Relative Translation Efficiency. We thereby elucidate that the dynamic adaptation of the tRNA pool is largely related to the proliferative state across tissues, which determines tissue-specific translation efficiency. Furthermore, the aberrant translational efficiency of ProCCA and GlyGGT in cancer, among other codons, which is partly regulated by the tRNA gene copy numbers and their promoter DNA methylation, is associated with poor patient survival.\n\nConclusionsThe distribution of tissue-specific tRNA pools over the whole cellular translatome affects the subsequent translational efficiency, which functionally determines a condition-specific expression program in tissues both in healthy and tumor states.

systems biology↗

bioRxiv2019

Impact of C-terminal amino acid composition on protein expression in bacteria

The C-terminal sequence of a protein is involved in processes such as efficiency of translation termination and protein degradation. However, the general relationship between features of this C-terminal sequence and levels of protein expression remains unknown. Here, we identified C-terminal amino acid biases that are ubiquitous across the bacterial taxonomy (1582 genomes). We showed that the frequency is higher for positively charged amino acids (lysine, arginine) while hydrophobic amino acids and threonine are lower. In highly abundant proteins, the C-terminal residue is more conserved. We then studied the impact of C-terminal composition on protein levels in a library of M. pneumoniae mutants, covering all possible combinations of the two last codons. We found that charged and polar residues, in particular lysine, led to higher expression, while hydrophobic and aromatic residues led to lower expression, with a difference in protein levels up to 4-fold. Our results demonstrate that the identity of the last amino acids has a strong influence on protein expression levels and is under selective pressure in highly expressed proteins.

systems biology↗

bioRxiv2019

SirT7 auto-ADP-ribosylation regulates glucose starvation response through macroH2A1.1

Sirtuins are key players in the response to oxidative, metabolic and genotoxic stress, and are involved in genome stability, metabolic homeostasis and aging. Originally described as NAD+-dependent deacetylases, some sirtuins are also characterized by a poorly understood mono-ADP-ribosyltransferase (mADPRT) activity. Here we report that the deacetylase SirT7 is a dual sirtuin as it also features auto-mADPRT activity. Molecular and structural evidence suggests that this novel activity occurs at a second previously undefined active site that is physically separated in another domain. Specific abrogation of this activity alters SirT7 chromatin distribution, suggesting a role for this modification in SirT7 chromatin binding specificity. We uncover an epigenetic pathway by which ADP-ribosyl-SirT7 is recognized by the ADP-ribose reader macroH2A1.1, a histone variant involved in chromatin organization, metabolism and differentiation. Glucose starvation (GS) boosts this interaction and promotes SirT7 relocalization to intergenic regions in a macroH2A1-dependent manner. Both SirT7 activities are in turn required to promote GS-dependent enrichment of macroH2A1 in a subset of nearby genes, which results in their specific up- or downregulation. Consistently, the expression changes of these genes associated to calorie restriction (CR) or aging are abrogated in SirT7-/- mice, reinforcing the link between Sirtuins, CR and aging. Our work provides a novel perspective about sirtuin duality and suggests a key role for SirT7/macroH2A1.1 axis in mammalian glucose homeostasis, calorie restriction signaling and aging.

molecular biology↗

bioRxiv2019

Proliferation specific codon usage facilitates oncogene translation

Tumors evolve under selection for gene mutations that give a growth advantage to the cancer cell. Intriguingly, some cancer genes are more often found mutated in tumors than their closely related family members. For example, KRAS mutations are more frequently observed in cancer in comparison to HRAS and NRAS. Here, we find that for RAS and six oncogene families, the most prevalent mutated members in cancer have a codon usage characteristic of genes involved in proliferation. The codon usage of KRAS is more adapted to be efficiently translated in proliferative cells than the codon usage of HRAS. We also show that the translation efficiency of KRAS varies between cell lines in a manner related to their tRNA expression. Altogether, our study demonstrates that a dynamic translation program contributes to shaping the expression profiles of oncogenes. We propose that codon bias related to cell proliferation contributes to the prevalence of mutations in certain members of oncogene families.

cancer biology↗

bioRxiv2018

VarQ: a tool for the structural analysis of Human Protein Variants

Understanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Even though there are several bioinformatic algorithms and servers that predict if a SAS can be pathogenic or not they give little or non-information on the actual effect on the protein function. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ Web Server is an online tool that given an UniProt id automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions among others. VarQ assessment was performed over a set of previously manually curated variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at http://varq.qb.fcen.uba.ar/.\n\nContact: lradusky@qb.fcen.uba.ar\n\nSupporting Information & Tutorials may be found in the webpage of the tool.

bioinformatics↗