Biology subjects

Chiva, C.

Publications and source records attributed to Chiva, C..

11 recordsLinked to original sources

bioRxiv2026

A generalizable normalization framework to decouple protocol and instrument effects: Application to high-sensitivity proteomics multicentric study (PME13)

Multicenter studies are essential for benchmarking analytical workflows, yet their interpretation is often confounded by the combined effects of experimental protocols and instrumentation. To address this challenge, we introduce a simple normalization-based analytical framework, the recovery metric ({rho}), designed to decouple protocol driven effects from instrument dependent variability. We applied this framework to the 13th Proteomics Multicentric Experiment (PME13), a large multicentric proteomics dataset generated across 27 laboratories using high sensitivity workflows and varying sample preparation protocols. By leveraging a common digested reference sample, {rho} enables direct cross-comparison of all datasets on a unified scale, effectively minimizing instrument-related biases. Using this approach, we demonstrate that apparent instrument dependent trends are largely removed when evaluated through {rho}, revealing consistent protocol driven effects across laboratories. Statistical modeling identified key variables influencing {rho}, including sample input amount, reduction and alkylation, and the use of n-dodecyl-{beta}-D-maltoside (DDM). While DDM was associated with improved {rho}, reduction and alkylation and additional handling steps led to reduced performance, particularly at low input levels. We further highlight practical considerations for the application of ratio based normalization, including the occurrence of values exceeding theoretical bounds, which reflect deviations from underlying assumptions and require appropriate filtering. Overall, this work establishes a generalizable analytical strategy for disentangling confounding factors in multicentric datasets and provides practical guidelines for optimizing high sensitivity proteomics (HSP) workflows. The proposed framework is broadly applicable to other analytical fields where cross laboratory comparability is required.

bioinformatics↗

bioRxiv2026

LFQ Benchmark Dataset - Generation Beta: Assessing Modern Proteomics Instruments and Acquisition Workflows with High-Throughput LC Gradients

Recent advances in liquid chromatography-mass spectrometry (LC-MS) have accelerated the adoption of high-throughput workflows that deliver deep proteome coverage using minimal sample amounts. This trend is largely driven by clinical and single-cell proteomics, where sensitivity and reproducibility are essential. Here, we extend our previous benchmark dataset (PXD028735) using next-generation LC-MS platforms optimized for rapid proteome analysis. We generated an extensive DDA/DIA dataset using a human-yeast-E. coli hybrid proteome. The proteome sample was distributed across multiple laboratories together with standardized analytical protocols specifying two short LC gradients (5 and 15 min) and low sample input amounts. This dataset includes data acquired on four different platforms, and features new scanning quadrupole-based implementations, extending coverage across different instruments and acquisition strategies. Our comprehensive evaluation highlights how technological advances and reduced LC gradients may affect proteome depth, quantitative precision, and cross-instrument consistency. The release of this benchmark dataset via ProteomeXchange (PXD070049 and PXD071205), allows for the acceleration of cross-platform algorithm development, enhance data mining strategies, and supports standardization of short-gradient, high-throughput LC-MS-based proteomics.

bioinformatics↗

bioRxiv2025

ProteoBench: the community-curated platform for comparing proteomics data analysis workflows

Mass spectrometry (MS)-based proteomics is a well-established strategy for analyzing complex biological mixtures. Many MS instruments and data acquisition strategies are available, and the data they acquire differ substantially, thus requiring tailored analysis algorithms. Hence, many dedicated bioinformatics workflows are developed. These are in constant evolution, and the community lacks a centralized platform for comparing their performance. Here, we propose ProteoBench, a single platform that brings together software developers and software users to provide an ever-evolving comparison of state-of-the-art proteomics data processing tools. ProteoBench is an open-source resource that enables the community to evaluate data analysis workflows, develop benchmarking modules dedicated to specific comparisons, and discuss the best methods to compare software tools. The platform ensures that the benchmark evolves alongside advances in proteomics data analysis workflows. ProteoBench guides researchers towards the best-suited tool and parameters for their specific project and data according to their needs, and developers can test their newly developed tools or workflows privately, before adding them as public references. This community-driven effort will increase transparency and reproducibility between MS data analysis workflows, as well as facilitate the development and publication of software workflows in the field.

bioinformatics↗

bioRxiv2025

Independent genomic trajectories shape adaptation to life on land across animal lineages

How animals repeatedly adapted to life on land is a central question in evolutionary biology. While terrestrialisation occurred independently across animal phyla, it remains unclear whether shared genomic mechanisms underlie these transitions. Here, we combine large-scale comparative genomics, machine learning, and multi-omics data, including proteomics and transcriptomics from stress experiments relevant to terrestrial environmental challenges in 17 species, to investigate the genomic basis of animal terrestrial adaptation. Gene co-expression networks reveal that genes relevant to stress are largely lineage-specific, yet converge in function through the co-option of gene families pre-dating terrestrialisation events. Phylogenomic and machine learning analyses support a dominant role for early-evolving genes, enriched in stress-related functions, paired with a higher gene loss than gain at terrestrialisation nodes. Our findings support a model of lineage-specific genomic changes involving mostly conserved genes that converged at the functional level during the independent transitions to terrestrial life.

evolutionary biology↗

bioRxiv2025

Proteome-wide multipoint internal calibration curves for mass spectrometry-based quantitative proteomics

Mass spectrometry (MS)-based proteomics is known for its high accuracy in quantifying peptides and proteins using various calibration strategies, including internal and external calibration curves. While external multi-point calibration curves are created from serial dilutions, they often fail to account for sample-specific matrix effects. In contrast, internal calibration curves account for sample matrix but face scalability and cost challenges for whole proteome analyses. In this manuscript we present a novel TMT-based multipoint internal calibration curve strategy, referred to as TMTCal, which enables the generation of internal calibration curves for all peptides identified within a proteome within a single experiment. We applied this strategy to human ovarian cancer cells to evaluate the linear quantitative responses of all the identified peptides and reveal the significant proteome changes associated with cisplatin treatment.

biochemistry↗

bioRxiv2025

A proteo-transcriptomic investigation of toxin evolution in planarians and their role in flatworm terrestrialization

The transition from aquatic to terrestrial environments represents a major evolutionary transition in animals, requiring significant adaptations in physiology and defense mechanisms to the challenges presented by the harsh terrestrial environment. Platyhelminthes, which include both aquatic and terrestrial species with a single terrestrialization event in the family Geoplaniidae, serve as excellent model organisms for studying the evolutionary adaptations required for terrestrialization. This study investigates the evolutionary dynamics of toxin orthologous groups (as a proxy to gene families) in aquatic and terrestrial flatworms, together with mucus composition, focusing on their role in terrestrialization from a molecular ecology perspective. Using a proteo-transcriptomic approach, we predicted and identified a broader toxin gene repertoire in terrestrial flatworms compared to freshwater ones. Although most toxins in flatworms arose before terrestrial planarian diversification--gaining a novel evolutionary origin at the Tricladida and Continenticola nodes--the mucus protein repertoire appears to have a far older evolutionary origin in both species. Moreover, distinct orthologous groups underpin the toxin gene repertoire and mucus composition in each lineage, highlighting the contrasting evolutionary trajectories of these two functional components. While toxin families in both aquatic and terrestrial flatworms revealed overall common functions, including cytokine modulation and ion channel regulation, terrestrial flatworms exhibited specific expansions of lectin-like proteins and pro-inflammatory responses, highlighting their potential key role to respond to land-based threats. This study provides new insights into the differential evolutionary trajectories of toxin and mucus proteins in planarians, offering a deeper understanding of the genetic innovations that facilitated flatworm terrestrialization.

evolutionary biology↗

bioRxiv2025

Genomic exaptation and regulatory landscape shifts as key mechanisms enabling flatworm terrestrialization

Understanding the genomic toolkit that facilitated animal terrestrialization--the transition from aquatic to terrestrial environments--is crucial for unravelling the evolutionary processes behind the origin and diversification of terrestrial biodiversity. Despite its significance, the genomic foundations driving the physiological and metabolic adaptations required for life on land remain largely unexplored across most terrestrial animal phyla. Planarians (phylum Platyhelminthes) represent an ideal model for studying terrestrialization, as only one terrestrial lineage, the family Geoplanidae (order Tricladida) is known to exist. Here, we used an integrative approach combining genomics, transcriptomics, and proteomics to investigate the genetic underpinnings potentially facilitating adaptation to terrestrial environments. Our analysis revealed a significant burst of gene gain preceding the diversification of terrestrial planarians and their split from freshwater relatives, in the branch leading to Tricladida. Upon exposure to abiotic stress, terrestrial and freshwater planarians exhibited distinct genetic toolkits: most differentially expressed genes emerged in orthologous groups gained specifically in the branch leading to Tricladida, over half of which showed signs of strong directional selection in terrestrial flatworms, indicating their adaptive importance for land colonization. Transcriptomic analyses further revealed contrasting stress responses: terrestrial planarians upregulated ancient genes whose origin predates the Geoplanidae lineage to cope with abiotic stress, while freshwater planarians downregulated a separate set of ancestral genes. Our genomic, transcriptomic, and proteomic data consistently show that the genetic toolkit for abiotic stress response in terrestrial planarians is highly differentiated from that of their freshwater counterparts, with significant regulatory shifts as well. Overall, our findings suggest a burst of gene gain in the Tricladida lineage, with co-option of these genes, rather than clade-specific innovations, playing a critical role in the origin and diversification of terrestrial flatworms. This underscores genomic exaptation and regulatory landscape shifts as key mechanisms enabling terrestrialization within Platyhelminthes. This study offers the first genome-wide insight into the genetic toolkit underlying flatworm terrestrialization and contributes broadly to understanding the genomic basis of animal terrestrialization.

evolutionary biology↗

bioRxiv2024

A multi-year longitudinal harmonization of quality controls in mass spectrometry proteomics core facilities

Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim to establish a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and we adopted a common processing software. We generated a 4-year longitudinal dataset from multiple instruments and laboratories, which enabled us to assess intra- and inter-laboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.

biochemistry↗

bioRxiv2021

Comparative proteogenomics deciphers the origin and evolution of eukaryotic chromatin

Histones and associated chromatin proteins have essential functions in eukaryotic genome organization and regulation. Despite this fundamental role in eukaryotic cell biology, we lack a phylogenetically-comprehensive understanding of chromatin evolution. Here, we combine comparative proteomics and genomics analysis of chromatin in eukaryotes and archaea. Proteomics uncovers the existence of histone post-translational modifications in Archaea. However, archaeal histone modifications are scarce, in contrast with the highly conserved and abundant marks we identify across eukaryotes. Phylogenetic analysis reveals that chromatin-associated catalytic functions (e.g., methyltransferases) have pre-eukaryotic origins, whereas histone mark readers and chaperones are eukaryotic innovations. We show that further chromatin evolution is characterized by expansion of readers, including capture by transposable elements and viruses. Overall, our study infers detailed evolutionary history of eukaryotic chromatin: from its archaeal roots, through the emergence of nucleosome-based regulation in the eukaryotic ancestor, to the diversification of chromatin regulators and their hijacking by genomic parasites.

evolutionary biology↗

bioRxiv2021

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Our transcriptomes reveal thousands of novel transcripts, some of them under active translation, expanding and completing the repertoire of primate gene models. Our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.

evolutionary biology↗

bioRxiv2020

Molecular characterization of triple negative breast cancer formaldehyde-fixed paraffin-embedded samples by data independent acquisition proteomics

Triple negative breast cancer (TNBC) accounts for 15-20% of all breast carcinomas and it is clinically characterized by an aggressive phenotype and bad prognosis. TNBC does not benefit from any targeted therapy, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of one hundred twenty-five formalin-fixed paraffin-embedded samples from patients diagnosed with triple negative breast cancer were analyzed by mass spectrometry using data-independent acquisition. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were used to characterize molecular groups. Additionally, a predictive signature related with relapse was defined. Two molecular groups with differences in several biological processes as glycolysis, translation and immune response, were defined in this cohort, and a prognostic signature based on the abundance of proteins RBM3 and NIPSNAP1 was defined. This predictor split the population into low-risk and high-risk groups. The differential processes identified between the two molecular groups may serve to design new therapeutic strategies in the future and the prognostic signature could be useful to identify a population at high-risk of relapse that could be directed to clinical trials.

cancer biology↗