Necrosulfonamide causes oxidation of PCM1 and impairs ciliogenesis and autophagy.

Centriolar satellites are high-order assemblies, scaffolded by the protein PCM1, that gravitate as particles around the centrosome and play pivotal roles in fundamental cellular processes notably ciliogenesis and autophagy. Despite stringent control mechanisms involving phosphorylation and ubiquitination, the landscape of post-translational modifications shaping these structures remains elusive. Here, we report that necrosulfonamide (NSA), a small molecule known for binding and inactivating the pivotal effector of cell death by necroptosis MLKL, intersects with centriolar satellites, ciliogenesis, and autophagy independently of MLKL. NSA functions as a potent redox cycler and triggers the oxidation and aggregation of PCM1 alongside select partners, while minimally impacting the overall distribution of centriolar satellites. Additionally, NSA-mediated ROS production disrupts ciliogenesis and leads to the accumulation of autophagy markers, partially alleviated by PCM1 deletion. Together, these results identify PCM1 as a redox sensor protein and provide new insights into the interplay between centriolar satellites and autophagy.

Leveraging the partition selection bias to achieve a high-quality clustering of mass spectra.

In proteomics, the identification of peptides from mass spectral data can be mathematically described as the partitioning of mass spectra into clusters (i.e., groups of spectra derived from the same peptide). The way partitions are validated is just as important, having evolved side by side with the clustering algorithms themselves and given rise to many partition assessment measures. An assessment measure is said to have a selection bias if, and only if, the probability that a randomly chosen partition scoring a high value depends on the number of clusters in the partition. In the context of clustering mass spectra, this might mislead the validation process to favor clustering algorithms that generate too many (or few) spectral clusters, regardless of the underlying peptide sequence. A selection bias toward the number of peptides is desirable for proteomics as it estimates the number of peptides in a complex protein mixture. Here, we introduce an assessment measure that is purposely biased toward the number of peptide ion species. We also introduce a partition assessment framework for proteomics, called the Partition Assessment Tool, and demonstrate its importance by evaluating the performance of eight clustering algorithms on seven proteomics datasets while discussing the trade-offs involved. SIGNIFICANCE: Clustering algorithms are widely adopted in proteomics for undertaking several tasks such as speeding up search engines, generating consensus mass spectra, and to aid in the classification of proteomic profiles. Choosing which algorithm is most fit for the task at hand is not simple as each algorithm has advantages and disadvantages; furthermore, specifying clustering parameters is also a necessary and fundamental step. For example, deciding on whether to generate "pure clusters" or fewer clusters but accepting noise. With this as motivation, we verify the performance of several widely adopted algorithms on proteomic datasets and introduce a theoretical framework for drawing conclusions on which approach is suitable for the task at hand.

TAK1 lessens the activity of the paracaspase MALT1 during T cell receptor signaling.

The CARMA1-BCL10-MALT1 (CBM) complex couples antigen receptors to the activation of Nuclear Factor κB (NF-κB) transcription factors in T/B lymphocytes. Within this signalosome, the MALT1 paracaspase serves dual roles: it is a crucial adaptor for signal transduction to NF-κB signaling, and a protease that shapes NF-κB activity and lymphocyte activation. Although a subtle choreography of ubiquitination and phosphorylation orchestrate the CBM, how precisely this complex and MALT1 enzyme are regulated continue to be elucidated. Here, we report that the chemical inhibition or the siRNA-based silencing of transforming growth factor beta-activated kinase 1 (TAK1), a known partner of the CBM complex required for NF-κB activation, enhanced the processing of MALT1 substrates. We further show that the assembly of the CBM as well as the ubiquitination of MALT1 was augmented when TAK1 was inhibited. Thus, TAK1 may initiate a negative feedback loop to finely tune the CBM complex activity.

Revisiting the Therapeutic Potential of Bothrops jararaca Venom: Screening for Novel Activities Using Connectivity Mapping.

Snake venoms are sources of molecules with proven and potential therapeutic applications. However, most activities assayed in venoms (or their components) are of hemorrhagic, hypotensive, edematogenic, neurotoxic or myotoxic natures. Thus, other relevant activities might remain unknown. Using functional genomics coupled to the connectivity map (C-map) approach, we undertook a wide range indirect search for biological activities within the venom of the South American pit viper Bothrops jararaca. For that effect, venom was incubated with human breast adenocarcinoma cell line (MCF7) followed by RNA extraction and gene expression analysis. A list of 90 differentially expressed genes was submitted to biosimilar drug discovery based on pattern recognition. Among the 100 highest-ranked positively correlated drugs, only the antihypertensive, antimicrobial (both antibiotic and antiparasitic), and antitumor classes had been previously reported for B. jararaca venom. The majority of drug classes identified were related to (1) antimicrobial activity; (2) treatment of neuropsychiatric illnesses (Parkinson's disease, schizophrenia, depression, and epilepsy); (3) treatment of cardiovascular diseases, and (4) anti-inflammatory action. The C-map results also indicated that B. jararaca venom may have components that target G-protein-coupled receptors (muscarinic, serotonergic, histaminergic, dopaminergic, GABA, and adrenergic) and ion channels. Although validation experiments are still necessary, the C-map correlation to drugs with activities previously linked to snake venoms supports the efficacy of this strategy as a broad-spectrum approach for biological activity screening, and rekindles the snake venom-based search for new therapeutic agents.

An in-depth snake venom proteopeptidome characterization: benchmarking Bothrops jararaca

A large-scale proteomic approach was devised to advance the understanding of venom composition. Bothrops jararaca venom was fractionated by OFFGEL followed by chromatography, generating peptidic and proteic fractions. The latter was submitted to trypsin digestion. Both fractions were separately analyzed by reversed-phase nanochromatography coupled to high resolution mass spectrometry. This strategy allowed deeper and joint characterizations of the peptidome and proteome (proteopeptidome) of this venom. Our results lead to the identification of 46 protein classes (with several uniquely assigned proteins per class) comprising eight high abundance bona fide venom components, and 38 additional classes in smaller quantities. This last category included previously described B. jararaca venom proteins, common Elapidae venom constituents (cobra venom factor and three-finger toxin), and proteins typically encountered in lysosomes, cellular membranes and blood plasma. Furthermore, this report is the most complete snake venom peptidome described so far, both in number of peptides and in variety of unique proteins that could have originated them. It is hypothesized that such diversity could enclose cryptides, whose bioactivities would contribute to envenomation in yet undetermined ways. Finally, we propose that the broad range screening of B. jararaca peptidome will facilitate the discovery of bioactive molecules, eventually leading to valuable therapeutical agents. Biological Significance: Our proteopeptidomic strategy yielded unprecedented insights into the remarkable diversity of B. jararaca venom composition, both at the peptide and protein levels. These results bring a substantial contribution to the actual pursuit of large-scale protein-level assignment in snake venomics. The detection of typical elapidic venom components, in a Viperidae venom, reinforces our view that the use of this approach (hand in-hand with transcriptomic and genomic data) for venom proteomic analysis, at the specimen-level, can greatly contribute for venom toxin evolution studies. Furthermore, data were generated in support of a previous hypothesis that venom gland secretory vesicles are specialized forms of lysosomes. Two testable hypotheses also emerge from the results of this work. The first is that a nucleobindin-2-derived protein could lead to prey disorientation during envenomation, aiding in its capture by the snake. The other being that the venom's peptidome might contain a population of cryptides, whose biological activities could lead to the development of new therapeutical agents.