Integrated analysis of whole blood oxylipin and cytokine responses after bacterial, viral, and T cell stimulation reveals new immune networks.

Oxylipins are major immunomodulating mediators, yet studies of inflammation focus mainly on cytokines. Here, using a standardized whole-blood stimulation system, we characterized the oxylipin-driven inflammatory responses to various stimuli and their relationships with cytokine responses. We performed a pilot study in 25 healthy individuals using 6 different stimuli: 2 bacterial stimuli (LPS and live BCG), 2 viral stimuli (vaccine-grade poly I:C and live H1N1 attenuated influenza), an enterotoxin superantigen and a Null control. All stimuli induced a strong production of oxylipins but most importantly, bacterial, viral, and T cell immune responses show distinct oxylipin signatures. Integration of the oxylipin and cytokine responses for each condition revealed new immune networks improving our understanding of inflammation regulation. Finally, the oxylipin responses and oxylipin-cytokine networks were compared in patients with active tuberculosis or with latent infection. This revealed different responses to BCG but not LPS stimulation highlighting new regulatory pathways for further investigations.

Census of exposed aggregation-prone regions in proteomes.

Loss of solubility usually leads to the detrimental elimination of protein function. In some cases, the protein aggregation is also required for beneficial functions. Given the duality of this phenomenon, it remains a fundamental question how natural selection controls the aggregation. The exponential growth of genomic sequence data and recent progress with in silico predictors of the aggregation allows approaching this problem by a large-scale bioinformatics analysis. Most of the aggregation-prone regions are hidden within the 3D structure, rendering them inaccessible for the intermolecular interactions responsible for aggregation. Thus, the most realistic census of the aggregation-prone regions requires crossing aggregation prediction with information about the location of the natively unfolded regions. This allows us to detect so-called 'exposed aggregation-prone regions' (EARs). Here, we analyzed the occurrence and distribution of the EARs in 76 reference proteomes from the three kingdoms of life. For this purpose, we used a bioinformatics pipeline, which provides a consensual result based on several predictors of aggregation. Our analysis revealed a number of new statistically significant correlations about the presence of EARs in different organisms, their dependence on protein length, cellular localizations, co-occurrence with short linear motifs and the level of protein expression. We also obtained a list of proteins with the conserved aggregation-prone sequences for further experimental tests. Insights gained from this work led to a deeper understanding of the relationship between protein evolution and aggregation.

TAPASS: Tool for annotation of protein amyloidogenicity in the context of other structural states.

Numerous studies have demonstrated that the propensity of a protein to form amyloids or amorphous aggregates is encoded by its amino acid sequence. This led to the emergence of several computational programs to predict amyloidogenicity from amino acid sequences. However, a growing number of studies indicate that an accurate prediction of the protein aggregation can only be achieved when also accounting for the overall structural context of the protein, and the likelihood of transition between the initial state and the aggregate. Here, we describe a computational pipeline called TAPASS, which was designed to do just that. The pipeline assigns each residue of a protein as belonging to a structured region or an intrinsically disordered region (IDR). For this purpose, TAPASS uses either several state-of-the-art programs for prediction of IDRs, of transmembrane regions and of structured domains or the artificial intelligence program AlphaFold. In the next step, this assignment is crossed with amyloidogenicity prediction. As a result, TAPASS allows the detection of Exposed Amyloidogenic Regions (EARs) located within intrinsically disordered regions (IDRs) and carrying high amyloidogenic potential. TAPASS can substantially improve the prediction of amyloids and be used in proteome-wide analysis to discover new amyloid-forming proteins. Its results, combined with clinical data, can create individual risk profiles for different amyloidoses, opening up new opportunities for personalised medicine. The architecture of the pipeline is designed so that it makes it easy to add new individual predictors as they become available. TAPASS can be used through the web interface (https://bioinfo.crbm.cnrs.fr/index.php?route=tools&tool=32).

Aspartate-phobia of thermophiles as a reaction to deleterious chemical transformations.

Prokaryotes growing at high temperatures have a high proportion of charged residues in their proteins to stabilize their 3D structure. By mining 175 disparate bacterial and archaeal proteomes we found that, against the general trend for charged residues, the frequency of aspartic acid residues decreases strongly as natural growth temperature increases. In search of the explanation, we hypothesized that the reason for such unusual correlation is the deleterious consequences of spontaneous chemical transformations of aspartate at high temperatures. Our subsequent statistical analysis supported this hypothesis. This finding reveals that organisms have likely adapted to high temperatures by minimizing the harmful consequences of spontaneous chemical transformations.

The hyperthermophilic archaeon Thermococcus kodakarensis is resistant to pervasive negative supercoiling activity of DNA gyrase.

In all cells, DNA topoisomerases dynamically regulate DNA supercoiling allowing essential DNA processes such as transcription and replication to occur. How this complex system emerged in the course of evolution is poorly understood. Intriguingly, a single horizontal gene transfer event led to the successful establishment of bacterial gyrase in Archaea, but its emergent function remains a mystery. To better understand the challenges associated with the establishment of pervasive negative supercoiling activity, we expressed the gyrase of the bacterium Thermotoga maritima in a naïve archaeon Thermococcus kodakarensis which naturally has positively supercoiled DNA. We found that the gyrase was catalytically active in T. kodakarensis leading to strong negative supercoiling of plasmid DNA which was stably maintained over at least eighty generations. An increased sensitivity of gyrase-expressing T. kodakarensis to ciprofloxacin suggested that gyrase also modulated chromosomal topology. Accordingly, global transcriptome analyses revealed large scale gene expression deregulation and identified a subset of genes responding to the negative supercoiling activity of gyrase. Surprisingly, the artificially introduced dominant negative supercoiling activity did not have a measurable effect on T. kodakarensis growth rate. Our data suggest that gyrase can become established in Thermococcales archaea without critically interfering with DNA transaction processes.

Δ133p53ß isoform pro-invasive activity is regulated through an aggregation-dependent mechanism in cancer cells.

The p53 isoform, Δ133p53ß, is critical in promoting cancer. Here we report that Δ133p53ß activity is regulated through an aggregation-dependent mechanism. Δ133p53ß aggregates were observed in cancer cells and tumour biopsies. The Δ133p53ß aggregation depends on association with interacting partners including p63 family members or the CCT chaperone complex. Depletion of the CCT complex promotes accumulation of Δ133p53ß aggregates and loss of Δ133p53ß dependent cancer cell invasion. In contrast, association with p63 family members recruits Δ133p53ß from aggregates increasing its intracellular mobility. Our study reveals novel mechanisms of cancer progression for p53 isoforms which are regulated through sequestration in aggregates and recruitment upon association with specific partners like p63 isoforms or CCT chaperone complex, that critically influence cancer cell features like EMT, migration and invasion.

Porins and Amyloids are Coded by Similar Sequence Motifs.

The relationship between amino acid sequences of the ß-hairpin structures and amyloidogenic ß-arcade-forming motifs are of special interest because, similar to amyloid fibrils, most of the ß-hairpin repeat (BHR) structures have the so-called cross-ß arrangement. Moreover, ß-hairpin is considered as a probable intermediate structure in amyloidogenesis. In this work, a bioinformatics sequence analysis of the known BHR structures is performed in search of amylodogenic motifs able to form ß-arcade fibrils. The analysis shows that the occurrence of the predicted ß-arcade motifs in the BHR regions is very different depending on the BHR structural fold, cellular localization, and phylogeny. One of the most striking observations is the high level of sequence similarity between the BHRs of membranous porins and ß-arcade motifs. This sequence similarity provides additional evidence that the structure of the membranous porins and annular amyloid oligomers may bear a resemblance. Moreover, these results explain how some amyloidogenic sequence can fold in either the ring-like shape oligomers or elongated amyloid fibrils. It has been also found that potentially lethal amyloidogenic ß-arcade motifs are absent in the elongated BHR structures of intracellular eukaryotic proteins. It allows to hypothesize that, in this case, the selective evolutionary pressure acts against aggregation.

Usage of a dataset of NMR resolved protein structures to test aggregation versus solubility prediction algorithms.

There has been an increased interest in computational methods for amyloid and (or) aggregate prediction, due to the prevalence of these aggregates in numerous diseases and their recently discovered functional importance. To evaluate these methods, several datasets have been compiled. Typically, aggregation-prone regions of proteins, which form aggregates or amyloids in vivo, are more than 15 residues long and intrinsically disordered. However, the number of such experimentally established amyloid forming and non-forming sequences are limited, not exceeding one hundred entries in existing databases. In this work, we parsed all available NMR-resolved protein structures from the PDB and assembled a new, sevenfold larger, dataset of unfolded sequences, soluble at high concentrations. We proposed to use these sequences as a negative set for evaluating methods for predicting aggregation in vivo. We also present the results of benchmarking cutting edge tools for the prediction of aggregation versus solubility propensity.