Brave new surfactant world revisited by thermoalkalophilic lipases: computational insights into the role of SDS as a substrate analog.

Non-ionic surfactants were shown to stabilize the active conformation of thermoalkalophilic lipases by mimicking the lipid substrate while the catalytic interactions formed by anionic surfactants have not been well characterized. In this study, we combined µs-scale molecular dynamics (MD) simulations and lipase activity assays to analyze the effect of ionic surfactant, sodium dodecyl sulfate (SDS), on the structure and activity of thermoalkalophilic lipases. Both the open and closed lipase conformations that differ in geometry were recruited to the MD analysis to provide a broader understanding of the molecular effect of SDS on the lipase structure. Simulations at 298 K showed the potential of SDS for maintaining the active lipase through binding to the sn-1 acyl-chain binding pocket in the open conformation or transforming the closed conformation to an open-like state. Consistent with MD findings, experimental analysis showed increased lipase activity upon SDS incubation at ambient temperature. Notably, the lipase cores stayed intact throughout 2 µs regardless of an increase in the simulation temperature or SDS concentration. However, the surface structures were unfolded in the presence of SDS and at elevated temperature for both conformations. Simulations of the dimeric lipase were also carried out and showed reduced flexibility of the surface structures which were unfolded in the monomer, indicating the insulating role of dimer interactions against SDS. Taken together, this study provides insights into the possible substrate mimicry by the ionic surfactant SDS for the thermoalkalophilic lipases without temperature elevation, underscoring SDS's potential for interfacial activation at ambient temperatures.

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium.

BACKGROUND: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. METHODS: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. RESULTS: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. CONCLUSIONS: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.

driveR: a novel method for prioritizing cancer driver genes using somatic genomics data.

BACKGROUND: Cancer develops due to "driver" alterations. Numerous approaches exist for predicting cancer drivers from cohort-scale genomics data. However, methods for personalized analysis of driver genes are underdeveloped. In this study, we developed a novel personalized/batch analysis approach for driver gene prioritization utilizing somatic genomics data, called driveR. RESULTS: Combining genomics information and prior biological knowledge, driveR accurately prioritizes cancer driver genes via a multi-task learning model. Testing on 28 different datasets, this study demonstrates that driveR performs adequately, achieving a median AUC of 0.684 (range 0.651-0.861) on the 28 batch analysis test datasets, and a median AUC of 0.773 (range 0-1) on the 5157 personalized analysis test samples. Moreover, it outperforms existing approaches, achieving a significantly higher median AUC than all of MutSigCV (Wilcoxon rank-sum test p < 0.001), DriverNet (p < 0.001), OncodriveFML (p < 0.001) and MutPanning (p < 0.001) on batch analysis test datasets, and a significantly higher median AUC than DawnRank (p < 0.001) and PRODIGY (p < 0.001) on personalized analysis datasets. CONCLUSIONS: This study demonstrates that the proposed method is an accurate and easy-to-utilize approach for prioritizing driver genes in cancer genomes in personalized or batch analyses. driveR is available on CRAN: https://cran.r-project.org/package=driveR .

Sequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma.

BACKGROUND: In the clinical setting, workflows for analyzing individual genomics data should be both comprehensive and convenient for clinical interpretation. In an effort for comprehensiveness and practicality, we attempted to create a clinical individual whole exome sequencing (WES) analysis workflow, allowing identification of genomic alterations and presentation of neurooncologically-relevant findings. METHODS: The analysis workflow detects germline and somatic variants and presents: (1) germline variants, (2) somatic short variants, (3) tumor mutational burden (TMB), (4) microsatellite instability (MSI), (5) somatic copy number alterations (SCNA), (6) SCNA burden, (7) loss of heterozygosity, (8) genes with double-hit, (9) mutational signatures, and (10) pathway enrichment analyses. Using the workflow, 58 WES analyses from matched blood and tumor samples of 52 patients were analyzed: 47 primary and 11 recurrent diffuse gliomas. RESULTS: The median mean read depths were 199.88 for tumor and 110.955 for normal samples. For germline variants, a median of 22 (14-33) variants per patient was reported. There was a median of 6 (0-590) reported somatic short variants per tumor. A median of 19 (0-94) broad SCNAs and a median of 6 (0-12) gene-level SCNAs were reported per tumor. The gene with the most frequent somatic short variants was TP53 (41.38%). The most frequent chromosome-/arm-level SCNA events were chr7 amplification, chr22q loss, and chr10 loss. TMB in primary gliomas were significantly lower than in recurrent tumors (p = 0.002). MSI incidence was low (6.9%). CONCLUSIONS: We demonstrate that WES can be practically and efficiently utilized for clinical analysis of individual brain tumors. The results display that NOTATES produces clinically relevant results in a concise but exhaustive manner.

Mutations and Copy Number Alterations in IDH Wild-Type Glioblastomas Are Shaped by Different Oncogenic Mechanisms.

Little is known about the mutational processes that shape the genetic landscape of gliomas. Numerous mutational processes leave marks on the genome in the form of mutations, copy number alterations, rearrangements or their combinations. To explore gliomagenesis, we hypothesized that gliomas with different underlying oncogenic mechanisms would have differences in the burden of various forms of these genomic alterations. This was an analysis on adult diffuse gliomas, but IDH-mutant gliomas as well as diffuse midline gliomas H3-K27M were excluded to search for the possible presence of new entities among the very heterogenous group of IDH-WT glioblastomas. The cohort was divided into two molecular subsets: (1) Molecularly-defined GBM (mGBM) as those that carried molecular features of glioblastomas (including TERT promoter mutations, 7/10 pattern, or EGFR-amplification), and (2) those who did not (others). Whole exome sequencing was performed for 37 primary tumors and matched blood samples as well as 8 recurrences. Single nucleotide variations (SNV), short insertion or deletions (indels) and copy number alterations (CNA) were quantified using 5 quantitative metrics (SNV burden, indel burden, copy number alteration frequency-wGII, chromosomal arm event ratio-CAER, copy number amplitude) as well as 4 parameters that explored underlying oncogenic mechanisms (chromothripsis, double minutes, microsatellite instability and mutational signatures). Findings were validated in the TCGA pan-glioma cohort. mGBM and "Others" differed significantly in their SNV (only in the TCGA cohort) and CNA metrics but not indel burden. SNV burden increased with increasing age at diagnosis and at recurrences and was driven by mismatch repair deficiency. On the contrary, indel and CNA metrics remained stable over increasing age at diagnosis and with recurrences. Copy number alteration frequency (wGII) correlated significantly with chromothripsis while CAER and CN amplitude correlated significantly with the presence of double minutes, suggesting separate underlying mechanisms for different forms of CNA.

Whole exome sequencing-based analysis to identify DNA damage repair deficiency as a major contributor to gliomagenesis in adult diffuse gliomas.

OBJECTIVE: Processes that cause or contribute to cancer, such as aging, exposure to carcinogens, or DNA damage repair deficiency (DDRd), create predictable and traceable nucleotide alterations in one's genetic code (termed "mutational signatures"). Large studies have previously identified various such mutational signatures across cancers that can be attributed to the specific causative processes. To gain further insight into the processes in glioma development, the authors analyzed mutational signatures in adult diffuse gliomas (DGs). METHODS: Twenty-five DGs and paired blood samples were whole exome sequenced. Somatic mutational signatures were identified using 2 different methods. Associations of the signatures with age at diagnosis, molecular subset, and mutational load were investigated. As DDRd-related signatures were frequently observed, germline and somatic DDR gene mutations as well as microsatellite instability (MSI) status were determined for all samples. For validation of signature prevalence, publicly available data from The Cancer Genome Atlas (TCGA) were used. RESULTS: Each tumor had a unique combination of signatures. The most common signatures were signature 1 (88%, aging related), signature 3 (52%, homologous recombination related), and signature 15 (56%, mismatch repair related). Eighty-four percent of the tumors contained at least 1 DDRd signature. The findings were validated using public TCGA data. The weight of signature 1 positively correlated with age (r = 0.43) while cumulative weight of DDRd signatures negatively correlated with age (r = -0.16). Each subject had at least 1 germline/somatic alteration in a DDR gene, the most common being the risk single nucleotide polymorphism rs1800734 in MLH1. The rs1800734-AA genotype had a higher cumulative DDRd weight as well as higher mutational load; TP53 was the most common somatically altered DDR gene. MSI was observed in 24% of the tumors. No significant associations of MSI status with mutational load, rs1800734, or the cumulative weight of DDRd signatures were identified. CONCLUSIONS: Current findings suggest that DDRd may act as a fundamental mechanism in gliomagenesis rather than being a random, secondary event.

First Report and In Silico Analysis of Leishmania virus (LRV2) identified in an autochthonous Leishmania major isolate in Turkey.

Leishmania virus (LRV) has previously been identified in different Leishmania species. Host-LRV interaction is associated with exacerbated clinical manifestations of cutaneous leishmaniasis (CL) and may cause poor therapeutic response. CL cases due to L. major with large skin lesions resistant to routine therapy were recently identified in Turkey. Here, we report the first autochthonous case of cutaneous leishmaniasis caused by LRV-positive Leishmania major, using conventional PCR targeting the viral capsid protein of LRV. The lesion of the case was 6 months old, relatively large (4 cm), and did not recover despite three consecutive intralesional applications of glucantime. Assessment of LRV's influence on prognosis and clinical outcomes of leishmaniasis, based on additional studies, is required.

IDH-mutant glioma specific association of rs55705857 located at 8q24.21 involves MYC deregulation.

The single nucleotide polymorphism rs55705857, located in a non-coding but evolutionarily conserved region at 8q24.21, is strongly associated with IDH-mutant glioma development and was suggested to be a causal variant. However, the molecular mechanism underlying this association has remained unknown. With a case control study in 285 gliomas, 316 healthy controls, 380 systemic cancers, 31 other CNS-tumors, and 120 IDH-mutant cartilaginous tumors, we identified that the association was specific to IDH-mutant gliomas. Odds-ratios were 9.25 (5.17-16.52; 95% CI) for IDH-mutated gliomas and 12.85 (5.94-27.83; 95% CI) for IDH-mutated, 1p/19q co-deleted gliomas. Decreasing strength with increasing anaplasia implied a modulatory effect. No somatic mutations were noted at this locus in 114 blood-tumor pairs, nor was there a copy number difference between risk-allele and only-ancestral allele carriers. CCDC26 RNA-expression was rare and not different between the two groups. There were only minor subtype-specific differences in common glioma driver genes. RNA sequencing and LC-MS/MS comparisons pointed to significantly altered MYC-signaling. Baseline enhancer activity of the conserved region specifically on the MYC promoter and its further positive modulation by the SNP risk-allele was shown in vitro. Our findings implicate MYC deregulation as the underlying cause of the observed association.

Zinc Modulates Self-Assembly of Bacillus thermocatenulatus Lipase.

Thermoalkalophilic lipases are prone to aggregation from their dimer interface to which structural zinc is very closely located. Structural zinc sites have been shown to induce protein aggregation, but the interaction between zinc and aggregation tendency in thermoalkalophilic lipases remains elusive. Here we delineate the interplay between zinc and aggregation of the lipase from Bacillus thermocatenulatus (BTL2), which is taken to be a representative of thermoalkalophilic lipase. Results showed that zinc removal disrupted the BTL2 dimer, leading to monomer formation and reduced thermostability manifesting as a link between zinc and dimerization that leads to thermostability, while zinc addition induced aggregation. Biochemical and kinetic characterizations of zinc-induced aggregates showed that the aggregates obtained from the early and late stages of aggregation had differential characteristics. In the early stages, the aggregates were soluble and possessed native-like structures, while in the late stages, the aggregates became insoluble and showed fibrillar characteristics with binding affinities for Congo red and thioflavin T. The impact of temperature on zinc-induced aggregation was further investigated, and it was found that the native-like early aggregates could completely dissociate into functional lipase forms at high temperatures while dissociation of the late aggregates was limited. To this end, we report that the zinc-induced aggregation of BTL2 can be reversed by temperature switches and initiated by ordered aggregates in the early stages that gain fibrillar-like features over time. Insights revealed by this work contributes to the knowledge of aggregation mechanisms that exist in thermophilic proteins, reflecting the potential use of metal addition and/or removal to fine-tune aggregation tendency.

CSF Proteomics Identifies Specific and Shared Pathways for Multiple Sclerosis Clinical Subtypes.

Multiple sclerosis (MS) is an immune-mediated, neuro-inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS) with a heterogeneous clinical presentation and course. There is a remarkable phenotypic heterogeneity in MS, and the molecular mechanisms underlying it remain unknown. We aimed to investigate further the etiopathogenesis related molecular pathways in subclinical types of MS using proteomic and bioinformatics approaches in cerebrospinal fluids of patients with clinically isolated syndrome, relapsing remitting MS and progressive MS (n=179). Comparison of disease groups with controls revealed a total of 151 proteins that are differentially expressed in clinically different MS subtypes. KEGG analysis using PANOGA tool revealed the disease related pathways including aldosterone-regulated sodium reabsorption (p=8.02x10-5) which is important in the immune cell migration, renin-angiotensin (p=6.88x10-5) system that induces Th17 dependent immunity, notch signaling (p=1.83x10-10) pathway indicating the activated remyelination and vitamin digestion and absorption pathways (p=1.73x10-5). An emerging theme from our studies is that whilst all MS clinical forms share common biological pathways, there are also clinical subtypes specific and pathophysiology related pathways which may have further therapeutic implications.

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for Galanthus L. using the relative complexity measure.

BACKGROUND: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. RESULT: In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. CONCLUSIONS: Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters.

The conserved lid tryptophan, W211, potentiates thermostability and thermoactivity in bacterial thermoalkalophilic lipases.

We hypothesize that aggregation of thermoalkalophilic lipases could be a thermostability mechanism. The conserved tryptophans (W211, W234) in the lid are of particular interest owing to their previous involvements in aggregation and thermostability mechanisms in many other proteins. The thermoalkalophilic lipase from Bacillus thermocatenulatus (BTL2) and its mutants (W211A, W234A) were expressed and purified to homogeneity. We found that, when aggregated, BTL2 is more thermostable than its non-aggregating form, showing that aggregation potentiates thermostability in the thermoalkalophilic lipase. Among the two lid mutants, the W211A lowered aggregation tendency drastically and resulted in a much less thermostable variant of BTL2, which indicated that W211 stabilizes the intermolecular interactions in BTL2 aggregates. Further thermoactivity and CD spectroscopy analyses showed that W211A also led to a strong decrease in the optimal and the melting temperature of BTL2, implying stabilization by W211 also to the intramolecular interactions. The other lid mutant W234A had no effects on these properties. Finally, we analyzed the molecular basis of these experimental findings in-silico using the dimer (PDB ID: 1KU0) and the monomer (PDB ID: 2W22) lipase structures. The computational analyses confirmed that W211 stabilized the intermolecular interactions in the dimer lipase and it is critical to the stability of the monomer lipase. Explicitly W211 confers stability to the dimer and the monomer lipase through distinct aromatic interactions with Y273-Y282 and H87-P232 respectively. The insights revealed by this work shed light not only on the mechanism of thermostability and its relation to aggregation but also on the particular role of the conserved lid tryptophan in the thermoalkalophilic lipases.