Stepwise emergence of the neuronal gene expression program in early animal evolution.

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

The Dynamic Regulatory Genome of Capsaspora and the Origin of Animal Multicellularity.

The unicellular ancestor of animals had a complex repertoire of genes linked to multicellular processes. This suggests that changes in the regulatory genome, rather than in gene innovation, were key to the origin of animals. Here, we carry out multiple functional genomic assays in Capsaspora owczarzaki, the unicellular relative of animals with the largest known gene repertoire for transcriptional regulation. We show that changing chromatin states, differential lincRNA expression, and dynamic cis-regulatory sites are associated with life cycle transitions in Capsaspora. Moreover, we demonstrate conservation of animal developmental transcription-factor networks and extensive network interconnection in this premetazoan organism. In contrast, however, Capsaspora lacks animal promoter types, and its regulatory sites are small, proximal, and lack signatures of animal enhancers. Overall, our results indicate that the emergence of animal multicellularity was linked to a major shift in genome cis-regulatory complexity, most notably the appearance of distal enhancer regulation.

Thymine DNA glycosylase regulates cell-cycle-driven p53 transcriptional control in pluripotent cells.

Cell cycle progression is linked to transcriptome dynamics and variations in the response of pluripotent cells to differentiation cues, mostly through unknown determinants. Here, we characterized the cell-cycle-associated transcriptome and proteome of mouse embryonic stem cells (mESCs) in naive ground state. We found that the thymine DNA glycosylase (TDG) is a cell-cycle-regulated co-factor of the tumor suppressor p53. Furthermore, TDG and p53 co-bind ESC-specific cis-regulatory elements and thereby control transcription of p53-dependent genes during self-renewal. We determined that the dynamic expression of TDG is required to promote the cell-cycle-associated transcriptional heterogeneity. Moreover, we demonstrated that transient depletion of TDG influences cell fate decisions during the early differentiation of mESCs. Our findings reveal an unanticipated role of TDG in promoting molecular heterogeneity during the cell cycle and highlight the central role of protein dynamics for the temporal control of cell fate during development.

IκB kinase-α coordinates BRD4 and JAK/STAT signaling to subvert DNA damage-based anticancer therapy.

Activation of the IκB kinase (IKK) complex has recurrently been linked to colorectal cancer (CRC) initiation and progression. However, identification of downstream effectors other than NF-κB has remained elusive. Here, analysis of IKK-dependent substrates in CRC cells after UV treatment revealed that phosphorylation of BRD4 by IKK-α is required for its chromatin-binding at target genes upon DNA damage. Moreover, IKK-α induces the NF-κB-dependent transcription of the cytokine LIF, leading to STAT3 activation, association with BRD4 and recruitment to specific target genes. IKK-α abrogation results in defective BRD4 and STAT3 functions and consequently irreparable DNA damage and apoptotic cell death upon different stimuli. Simultaneous inhibition of BRAF-dependent IKK-α activity, BRD4, and the JAK/STAT pathway enhanced the therapeutic potential of 5-fluorouracil combined with irinotecan in CRC cells and is curative in a chemotherapy-resistant xenograft model. Finally, coordinated expression of LIF and IKK-α is a poor prognosis marker for CRC patients. Our data uncover a functional link between IKK-α, BRD4, and JAK/STAT signaling with clinical relevance.

IKKα Kinase Regulates the DNA Damage Response and Drives Chemo-resistance in Cancer.

Phosphorylated IKKα(p45) is a nuclear active form of the IKKα kinase that is induced by the MAP kinases BRAF and TAK1 and promotes tumor growth independent of canonical NF-κB signaling. Insights into the sources of IKKα(p45) activation and its downstream substrates in the nucleus remain to be defined. Here, we discover that IKKα(p45) is rapidly activated by DNA damage independent of ATM-ATR, but dependent on BRAF-TAK1-p38-MAPK, and is required for robust ATM activation and efficient DNA repair. Abolishing BRAF or IKKα activity attenuates ATM, Chk1, MDC1, Kap1, and 53BP1 phosphorylation, compromises 53BP1 and RIF1 co-recruitment to sites of DNA lesions, and inhibits 53BP1-dependent fusion of dysfunctional telomeres. Furthermore, IKKα or BRAF inhibition synergistically enhances the therapeutic potential of 5-FU and irinotecan to eradicate chemotherapy-resistant metastatic human tumors in vivo. Our results implicate BRAF and IKKα kinases in the DDR and reveal a combination strategy for cancer treatment.

Author Correction: The dental proteome of Homo antecessor.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The dental proteome of Homo antecessor.

The phylogenetic relationships between hominins of the Early Pleistocene epoch in Eurasia, such as Homo antecessor, and hominins that appear later in the fossil record during the Middle Pleistocene epoch, such as Homo sapiens, are highly debated1-5. For the oldest remains, the molecular study of these relationships is hindered by the degradation of ancient DNA. However, recent research has demonstrated that the analysis of ancient proteins can address this challenge6-8. Here we present the dental enamel proteomes of H. antecessor from Atapuerca (Spain)9,10 and Homo erectus from Dmanisi (Georgia)1, two key fossil assemblages that have a central role in models of Pleistocene hominin morphology, dispersal and divergence. We provide evidence that H. antecessor is a close sister lineage to subsequent Middle and Late Pleistocene hominins, including modern humans, Neanderthals and Denisovans. This placement implies that the modern-like face of H. antecessor-that is, similar to that of modern humans-may have a considerably deep ancestry in the genus Homo, and that the cranial morphology of Neanderthals represents a derived form. By recovering AMELY-specific peptide sequences, we also conclude that the H. antecessor molar fragment from Atapuerca that we analysed belonged to a male individual. Finally, these H. antecessor and H. erectus fossils preserve evidence of enamel proteome phosphorylation and proteolytic digestion that occurred in vivo during tooth formation. Our results provide important insights into the evolutionary relationships between H. antecessor and other hominin groups, and pave the way for future studies using enamel proteomes to investigate hominin biology across the existence of the genus Homo.

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. Around half of the captured isoforms are not annotated in their reference genomes, significantly expanding the gene models in primates. Furthermore, our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these evolutionary 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.

Updated MS²PIP web server supports cutting-edge proteomics applications.

Interest in the use of machine learning for peptide fragmentation spectrum prediction has been strongly on the rise over the past years, especially for applications in challenging proteomics identification workflows such as immunopeptidomics and the full-proteome identification of data independent acquisition spectra. Since its inception, the MS²PIP peptide spectrum predictor has been widely used for various downstream applications, mostly thanks to its accuracy, ease-of-use, and broad applicability. We here present a thoroughly updated version of the MS²PIP web server, which includes new and more performant prediction models for both tryptic- and non-tryptic peptides, for immunopeptides, and for CID-fragmented TMT-labeled peptides. Additionally, we have also added new functionality to greatly facilitate the generation of proteome-wide predicted spectral libraries, requiring only a FASTA protein file as input. These libraries also include retention time predictions from DeepLC. Moreover, we now provide pre-built and ready-to-download spectral libraries for various model organisms in multiple DIA-compatible spectral library formats. Besides upgrading the back-end models, the user experience on the MS²PIP web server is thus also greatly enhanced, extending its applicability to new domains, including immunopeptidomics and MS3-based TMT quantification experiments. MS²PIP is freely available at https://iomics.ugent.be/ms2pip/.

Dynamic interplay between RPL3- and RPL3L-containing ribosomes modulates mitochondrial activity in the mammalian heart.

The existence of naturally occurring ribosome heterogeneity is now a well-acknowledged phenomenon. However, whether this heterogeneity leads to functionally diverse 'specialized ribosomes' is still a controversial topic. Here, we explore the biological function of RPL3L (uL3L), a ribosomal protein (RP) paralogue of RPL3 (uL3) that is exclusively expressed in skeletal muscle and heart tissues, by generating a viable homozygous Rpl3l knockout mouse strain. We identify a rescue mechanism in which, upon RPL3L depletion, RPL3 becomes up-regulated, yielding RPL3-containing ribosomes instead of RPL3L-containing ribosomes that are typically found in cardiomyocytes. Using both ribosome profiling (Ribo-seq) and a novel orthogonal approach consisting of ribosome pulldown coupled to nanopore sequencing (Nano-TRAP), we find that RPL3L modulates neither translational efficiency nor ribosome affinity towards a specific subset of transcripts. In contrast, we show that depletion of RPL3L leads to increased ribosome-mitochondria interactions in cardiomyocytes, which is accompanied by a significant increase in ATP levels, potentially as a result of fine-tuning of mitochondrial activity. Our results demonstrate that the existence of tissue-specific RP paralogues does not necessarily lead to enhanced translation of specific transcripts or modulation of translational output. Instead, we reveal a complex cellular scenario in which RPL3L modulates the expression of RPL3, which in turn affects ribosomal subcellular localization and, ultimately, mitochondrial activity.

Ribosomes are macromolecular machines responsible for protein synthesis in all living beings. Recent studies have shown that ribosomes can be heterogeneous in their structure, possibly leading to a specialized function. Here, we focus on RPL3L, a ribosomal protein expressed exclusively in striated muscles. We find that the deletion of the Rpl3l gene in a mouse model triggers a compensation mechanism, in which the missing RPL3L protein is replaced by its paralogue, RPL3. Furthermore, we find that RPL3-containing ribosomes establish closer interactions with mitochondria, cellular organelles responsible for energy production, leading to higher energy production when compared with RPL3L-containing ribosomes. Finally, we show that the RPL3­RPL3L compensation mechanism is also triggered in heart disease conditions, such as hypertrophy and myocardial infarction.

Spectral libraries from nucleobases and deoxyribonucleosides facilitate the identification of ribonucleosides by nano-flow liquid chromatography-tandem mass spectrometry.

RATIONALE: The study addresses the challenge of identifying RNA post-transcriptional modifications when commercial standards are not available to generate reference spectral libraries. It proposes employing homologous nucleobases and deoxyribonucleosides as alternative reference spectral libraries to aid in identifying modified ribonucleosides and distinguishing them from their positional isomers when the standards are unavailable. METHODS: Complete sets of ribonucleoside, deoxyribonucleoside and nucleobase standards were analyzed using high-performance nano-flow liquid chromatography coupled to an Orbitrap Eclipse Tribrid mass spectrometer. Spectral libraries were constructed from homologous nucleobases and deoxyribonucleosides using targeted MS2 and neutral-loss-triggered MS3 methods, and collision energies were optimized. The feasibility of using these libraries for identifying modified ribonucleosides and their positional isomers was assessed through comparison of spectral fragmentation patterns. RESULTS: Our analysis reveals that both MS2 and neutral-loss-triggered MS3 methods yielded rich spectra with similar fragmentation patterns across ribonucleosides, deoxyribonucleosides and nucleobases. Moreover, we demonstrate that spectra from nucleobases and deoxyribonucleosides, generated at optimized collision energies, exhibited sufficient similarity to those of modified ribonucleosides to enable their use as reference spectra for accurate identification of positional isomers within ribonucleoside families. CONCLUSIONS: The study demonstrates the efficacy of utilizing homologous nucleobases and deoxyribonucleosides as interchangeable reference spectral libraries for identifying modified ribonucleosides and their positional isomers. This approach offers a valuable solution for overcoming limitations posed by the unavailability of commercial standards, enhancing the analysis of RNA post-transcriptional modifications via mass spectrometry.

Mass Spectrometry Identification of Biomarkers in Extracellular Vesicles From Plasmodium vivax Liver Hypnozoite Infections.

Latent liver stages termed hypnozoites cause relapsing Plasmodium vivax malaria infection and represent a major obstacle in the goal of malaria elimination. Hypnozoites are clinically undetectable, and presently, there are no biomarkers of this persistent parasite reservoir in the human liver. Here, we have identified parasite and human proteins associated with extracellular vesicles (EVs) secreted from in vivo infections exclusively containing hypnozoites. We used P. vivax-infected human liver-chimeric (huHEP) FRG KO mice treated with the schizonticidal experimental drug MMV048 as hypnozoite infection model. Immunofluorescence-based quantification of P. vivax liver forms showed that MMV048 removed schizonts from chimeric mice livers. Proteomic analysis of EVs derived from FRG huHEP mice showed that human EV cargo from infected FRG huHEP mice contain inflammation markers associated with active schizont replication and identified 66 P. vivax proteins. To identify hypnozoite-specific proteins associated with EVs, we mined the proteome data from MMV048-treated mice and performed an analysis involving intragroup and intergroup comparisons across all experimental conditions followed by a peptide compatibility analysis with predicted spectra to warrant robust identification. Only one protein fulfilled this stringent top-down selection, a putative filamin domain-containing protein. This study sets the stage to unveil biological features of human liver infections and identify biomarkers of hypnozoite infection associated with EVs.

Melanoma RBPome identification reveals PDIA6 as an unconventional RNA-binding protein involved in metastasis.

RNA-binding proteins (RBPs) have been relatively overlooked in cancer research despite their contribution to virtually every cancer hallmark. Here, we use RNA interactome capture (RIC) to characterize the melanoma RBPome and uncover novel RBPs involved in melanoma progression. Comparison of RIC profiles of a non-tumoral versus a metastatic cell line revealed prevalent changes in RNA-binding capacities that were not associated with changes in RBP levels. Extensive functional validation of a selected group of 24 RBPs using five different in vitro assays unveiled unanticipated roles of RBPs in melanoma malignancy. As proof-of-principle we focused on PDIA6, an ER-lumen chaperone that displayed a novel RNA-binding activity. We show that PDIA6 is involved in metastatic progression, map its RNA-binding domain, and find that RNA binding is required for PDIA6 tumorigenic properties. These results exemplify how RIC technologies can be harnessed to uncover novel vulnerabilities of cancer cells.

MSstatsShiny: A GUI for Versatile, Scalable, and Reproducible Statistical Analyses of Quantitative Proteomic Experiments.

Liquid chromatography coupled with bottom-up mass spectrometry (LC-MS/MS)-based proteomics is a versatile technology for identifying and quantifying proteins in complex biological mixtures. Postidentification, analysis of changes in protein abundances between conditions requires increasingly complex and specialized statistical methods. Many of these methods, in particular the family of open-source Bioconductor packages MSstats, are implemented in a coding language such as R. To make the methods in MSstats accessible to users with limited programming and statistical background, we have created MSstatsShiny, an R-Shiny graphical user interface (GUI) integrated with MSstats, MSstatsTMT, and MSstatsPTM. The GUI provides a point and click analysis pipeline applicable to a wide variety of proteomics experimental types, including label-free data-dependent acquisitions (DDAs) or data-independent acquisitions (DIAs), or tandem mass tag (TMT)-based TMT-DDAs, answering questions such as relative changes in the abundance of peptides, proteins, or post-translational modifications (PTMs). To support reproducible research, the application saves user's selections and builds an R script that programmatically recreates the analysis. MSstatsShiny can be installed locally via Github and Bioconductor, or utilized on the cloud at www.msstatsshiny.com. We illustrate the utility of the platform using two experimental data sets (MassIVE IDs MSV000086623 and MSV000085565).

MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale.

The MSstats R-Bioconductor family of packages is widely used for statistical analyses of quantitative bottom-up mass spectrometry-based proteomic experiments to detect differentially abundant proteins. It is applicable to a variety of experimental designs and data acquisition strategies and is compatible with many data processing tools used to identify and quantify spectral features. In the face of ever-increasing complexities of experiments and data processing strategies, the core package of the family, with the same name MSstats, has undergone a series of substantial updates. Its new version MSstats v4.0 improves the usability, versatility, and accuracy of statistical methodology, and the usage of computational resources. New converters integrate the output of upstream processing tools directly with MSstats, requiring less manual work by the user. The package's statistical models have been updated to a more robust workflow. Finally, MSstats' code has been substantially refactored to improve memory use and computation speed. Here we detail these updates, highlighting methodological differences between the new and old versions. An empirical comparison of MSstats v4.0 to its previous implementations, as well as to the packages MSqRob and DEqMS, on controlled mixtures and biological experiments demonstrated a stronger performance and better usability of MSstats v4.0 as compared to existing methods.

Assessment and Prediction of Human Proteotypic Peptide Stability for Proteomics Quantification.

Mass spectrometry coupled to liquid chromatography is one of the most powerful technologies for proteome quantification in biomedical samples. In peptide-centric workflows, protein mixtures are enzymatically digested to peptides prior their analysis. However, proteome-wide quantification studies rarely identify all potential peptides for any given protein, and targeted proteomics experiments focus on a set of peptides for the proteins of interest. Consequently, proteomics relies on the use of a limited subset of all possible peptides as proxies for protein quantitation. In this work, we evaluated the stability of the human proteotypic peptides during 21 days and trained a deep learning model to predict peptide stability directly from tryptic sequences, which together constitute a resource of broad interest to prioritize and select peptides in proteome quantification experiments.

MassIVE.quant: a community resource of quantitative mass spectrometry-based proteomics datasets.

MassIVE.quant is a repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics, which is compatible with all mass spectrometry data acquisition types and computational analysis tools. A branch structure enables MassIVE.quant to systematically store raw experimental data, metadata of the experimental design, scripts of the quantitative analysis workflow, intermediate input and output files, as well as alternative reanalyses of the same dataset.

Beauveria bassiana rewires molecular mechanisms related to growth and defense in tomato.

Plant roots can exploit beneficial associations with soil-inhabiting microbes, promoting growth and expanding the immune capacity of the host plant. In this work, we aimed to provide new information on changes occurring in tomato interacting with the beneficial fungus Beauveria bassiana. The tomato leaf proteome revealed perturbed molecular pathways during the establishment of the plant-fungus relationship. In the early stages of colonization (5-7 d), proteins related to defense responses to the fungus were down-regulated and proteins related to calcium transport were up-regulated. At later time points (12-19 d after colonization), up-regulation of molecular pathways linked to protein/amino acid turnover and to biosynthesis of energy compounds suggests beneficial interaction enhancing plant growth and development. At the later stage, the profile of leaf hormones and related compounds was also investigated, highlighting up-regulation of those related to plant growth and defense. Finally, B. bassiana colonization was found to improve plant resistance to Botrytis cinerea, impacting plant oxidative damage. Overall, our findings further expand current knowledge on the possible mechanisms underlying the beneficial role of B. bassiana in tomato plants.

Quality standards in proteomics research facilities: Common standards and quality procedures are essential for proteomics facilities and their users.

Proteomics research infrastructures and core facilities within the Core for Life alliance advocate for community policies for quality control to ensure high standards in proteomics services.

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

Triple negative breast cancer accounts for 15%-20% of all breast carcinomas and is clinically characterized by an aggressive phenotype and poor prognosis. Triple negative tumors do not benefit from targeted therapies, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of 125 formalin-fixed paraffin-embedded samples from patients diagnosed with non-metastatic triple negative breast cancer were analyzed using data-independent acquisition + in a LTQ-Orbitrap Fusion Lumos mass spectrometer coupled to an EASY-nLC 1000. 1206 proteins were identified in at least 66% of the samples. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were combined to characterize proteomics-based molecular groups. Two molecular groups were defined with differences in biological processes such as glycolysis, translation and immune response. These two molecular groups showed also several differentially expressed proteins. This clinically homogenous dataset may serve to design new therapeutic strategies in the future.