Bacterial Virulence and Prevention for Human Spaceflight.

With the advancement in reusable rocket propulsion technology, space tourist trips into outer space are now becoming a possibility at a cost-effective rate. As such, astronauts will face a host of health-related challenges, particularly on long-duration space missions where maintaining a balanced healthy microbiome is going to be vital for human survival in space exploration as well as mission success. The human microbiome involves a whole list of micro-organisms that reside in and on the human host, and plays an integral role in keeping the human host healthy. However, imbalances in the microbiome have been directly linked to many human diseases. Research findings have clearly shown that the outer space environment can directly affect the normal microbiome of astronauts when the astronaut is exposed to the microgravity environment. In this study, we show that the simulation of microgravity on earth can mimic the outer space microgravity environment. Staphylococus aureus (S. aureus) was chosen for this study as it is an opportunistic pathogen, which is part of the normal human skin microflora and the nasal passages. This study's results show that S. aureus proliferation was significantly increased under a microgravity environment compared to Earth's gravity conditions, which complements previous work performed on bacteria in the outer space environment in the International Space Station (ISS). This demonstrates that this technology can be utilised here on Earth to mimic the outer space environment and to study challenging health-related questions. This in return saves us the cost on conducting experiments in the ISS and can help advance knowledge at a faster rate and produce countermeasures to mitigate the negative side effects of the hostile outer space environment on humans.

Relationship between location of epileptic focus and occurrence during sleep versus wakefulness.

Different sleep stages exert differential effects on interictal discharges, neural synchrony and seizure threshold. We sought to assess the relationship between localization of the epileptogenic focus and seizure distribution in sleep versus wakefulness among patients with refractory epilepsy. We conducted a retrospective chart review-based study. Video-electroencephalography of patients with refractory epilepsy, planned for resective surgery, were reviewed for seizure localisation and occurrence relative to stage of sleep/wakefulness. Demographic/clinical data, including details of surgery, were also recorded. Bivariate analysis was conducted using the chi-square test for proportions and unpaired t-test/ANOVA to compare the means within groups. We enrolled 175 patients (107 males) with a mean age of 26.1 + 9.8 years (range: 4-53 years). We analysed 1,282 seizures, of which 916 (71.5%) were temporal, 95 (7.4%) frontal, 144 (11.2 %) central/ parietal and 19 (1.5%) arose from the occipital lobe. Temporal lobe onset seizures were more frequent during wakefulness (77.7%) compared to extra-temporal localization (65%) (p<0.0001). Amongst temporal lobe onset seizures, those during wakefulness arose more frequently from the lateral temporal (88.6%) compared to the mesial temporal lobe (75.5%) (p=0.0003). A higher proportion of seizures evolved into secondary generalisation during sleep (23.5%) versus 8.7% during wakefulness (p<0.0001). Our study demonstrates that lobar location of epileptogenic foci is associated with a predilection of seizures to occur, as well as secondarily generalise, during sleep/wakefulness. Seizures with lateral temporal lobe as well as extratemporal lobe onset were more likely to occur during wakefulness. Overall, sleep related seizures were more likely to be of extratemporal lobe onset, though.

The neoepitope landscape of breast cancer: implications for immunotherapy.

BACKGROUND: Cancer immunotherapy with immune checkpoint blockade (CKB) is now standard of care for multiple cancers. The clinical response to CKB is associated with T cell immunity targeting cancer-induced mutations that generate novel HLA-binding epitopes (neoepitopes). METHODS: Here, we developed a rapid bioinformatics pipeline and filtering strategy, EpitopeHunter, to identify and prioritize clinically relevant neoepitopes from the landscape of somatic mutations. We used the pipeline to determine the frequency of neoepitopes from the TCGA dataset of invasive breast cancers. We predicted HLA class I-binding neoepitopes for 870 breast cancer samples and filtered the neoepitopes based on tumor transcript abundance. RESULTS: We found that the total mutational burden (TMB) was highest for triple-negative breast cancer, TNBC, (median = 63 mutations, range: 2-765); followed by HER-2(+) (median = 39 mutations, range: 1-1206); and lowest for ER/PR(+)HER-2(-) (median = 32 mutations, range: 1-2860). 40% of the nonsynonymous mutations led to the generation of predicted neoepitopes. The neoepitope load (NEL) is highly correlated with the mutational burden (R2 = 0.86). CONCLUSIONS: Only half (51%) of the predicted neoepitopes are expressed at the RNA level (FPKM≥2), indicating the importance of assessing whether neoepitopes are transcribed. However, of all patients, 93% have at least one expressed predicted neoepitope, indicating that most breast cancer patients have the potential for neo-epitope targeted immunotherapy.

Human Papilloma Virus Specific Immunogenicity and Dysfunction of CD8+ T Cells in Head and Neck Cancer.

Human papillomavirus subtype 16 (HPV16) is the primary cause of an increasing number of head and neck squamous cell carcinomas (HNSCC), providing strong rationale for T-cell immune therapies against HPV+ HNSCC. Here we assess immunogenicity of HPV16-specific CD8+ T cells (CTL) and characterize HPV-specific mechanisms of T-cell dysfunction. We identified 16 strong and 29 moderately immunogenic CTL-epitopes from HPV16 E2, E6, and E7 antigens restricted by 12 common HLA class I alleles. E2-specific CTL-reactivity was higher in patients with HPV+ HNSCC than in healthy controls (>3-fold; P = 0.026). Patient-derived E2, E6, and E7 peripheral CTLs exhibited heterogeneity in dysfunctional phenotypes. Immunogenomic analyses of 119 HNSCC transcriptomes revealed high T-cell infiltration and dysfunction in HPV+ HNSCC and correlation of HPV antigen expression with T-cell exhaustion gene signatures. Indoleamine 2,3-dioxygenase (IDO-1) was strongly expressed in HPV+ HNSCC versus HPV- HNSCC (P = 0.001) and correlated with E7 expression (R 2 = 0.84; P = 0.033). Combination treatment with PD-1 blockade and IDO-1 inhibition overcame profound CTL-dysfunction, enhancing HPV+ HNSCC sensitivity to CTL-cytotoxicity in vitro (up to 10-fold in E7-CTLs, P = 0.011). Our findings implicate mechanisms of T-cell escape in HPV+ HNSCC, wherein high tumoral HPV-antigen load results in high expression of immune dysfunction genes on tumor cells (e.g., IDO-1), and dysfunction of HPV-specific CTLs (e.g., E7, E2-CTLs). The HPV16 CTL-epitopes identified in this study, in combination with blockade of HPV+ HNSCC-specific PD-1/IDO-1 checkpoints, may be useful for targeted immunotherapy.Significance: This study evaluates the HPV antigen T-cell immunogenicity role of inhibitory receptors and other exhaustion markers in the cytotoxic function of HPV antigen-specific CTLs and identifies combined inhibition of PD-1/IDO-1 as a strategy to enhance CTL targeting of HPV+ HNSCC. Cancer Res; 78(21); 6159-70. ©2018 AACR.

The association of genomic lesions and PD-1/PD-L1 expression in resected triple-negative breast cancers.

BACKGROUND: Elevated PD-L1 expression on tumor cells, a context associated with an adaptive immune response, has been linked to the total burden of copy number variants (CNVs) in aneuploid tumors, to microsatellite instability (MSI), and to specific genomic driver lesions, including loss of PTEN, MYC amplification, and activating mutations in driver oncogenes such as KRAS and PIK3CA. Triple-negative breast cancers (TNBCs) typically have high levels of CNVs and diverse driver lesions in their genomes. Thus, there is significant interest in exploiting genomic data to develop predictive immunotherapy biomarkers for patients with TNBC. METHODS: Whole tissue samples from 55 resected TNBCs were screened by immunohistochemistry (IHC) for PD-1 and PD-L1 by using validated antibodies and established scoring methods for staining of tumor and non-tumor cells. In parallel, we interrogated biopsies from each resection with DNA content flow cytometry and sorted the nuclei of diploid, tetraploid, and aneuploid cell populations. CNVs were mapped with CNV oligonucleotide arrays by using purified (>95%) tumor populations. We generated whole exome data for 12 sorted tumor samples to increase the resolution within loci of interest and to incorporate somatic mutations into our genomic signatures. RESULTS AND CONCLUSIONS: PD-L1 staining was detected on tumor cells in 29 out of 54 (54%) evaluable cases and was associated with increased overall survival (P = 0.0024). High levels of PD-1 and PD-L1 (IHC ≥4) were present in 11 out of 54 (20%) and 20 out of 54 (37%) cases with staining of PD-L1 primarily on tumor cells for 17 out of 20 (85%) cases. The latter included tumors with both high (>50) and low (<20) numbers of CNVs. Notably, homozygous deletion of PTEN (n = 6) or activating mutation in PIK3CA (n = 1) was not associated with increased expression of either immune checkpoint activator in TNBC. In contrast, two treatment-naïve cases with EGFR driver amplicons had high PD-L1 tumor staining. High mutational load and predicted neoepitopes were observed in MSI+ and high CNV burden TNBCs but were not associated with high PD-L1 expression on tumor cells. Our results challenge current models of genomic-based immunotherapy signatures yet suggest that discrete genomic lesions may complement existing biomarkers to advance immune checkpoint therapies for patients with TNBC.

Variable Autosomal and X Divergence Near and Far from Genes Affects Estimates of Male Mutation Bias in Great Apes.

Male mutation bias, when more mutations are passed on via the male germline than via the female germline, is observed across mammals. One common way to infer the magnitude of male mutation bias, α, is to compare levels of neutral sequence divergence between genomic regions that spend different amounts of time in the male and female germline. For great apes, including human, we show that estimates of divergence are reduced in putatively unconstrained regions near genes relative to unconstrained regions far from genes. Divergence increases with increasing distance from genes on both the X chromosome and autosomes, but increases faster on the X chromosome than autosomes. As a result, ratios of X/A divergence increase with increasing distance from genes and corresponding estimates of male mutation bias are significantly higher in intergenic regions near genes versus far from genes. Future studies in other species will need to carefully consider the effect that genomic location will have on estimates of male mutation bias.

Integrating virtual and biochemical screening for protein tyrosine phosphatase inhibitor discovery.

Protein tyrosine phosphatases (PTPs) represent an important class of enzymes that mediate signal transduction and control diverse aspects of cell behavior. The importance of their activity is exemplified by their significant contribution to disease etiology with over half of all human PTP genes implicated in at least one disease. Small molecule inhibitors targeting individual PTPs are important biological tools, and are needed to fully characterize the function of these enzymes. Moreover, potent and selective PTP inhibitors hold the promise to transform the treatment of many diseases. While numerous methods exist to develop PTP-directed small molecules, we have found that complimentary use of both virtual (in silico) and biochemical (in vitro) screening approaches expedite compound identification and drug development. Here, we summarize methods pertinent to our work and others. Focusing on specific challenges and successes we have experienced, we discuss the considerable caution that must be taken to avoid enrichment of inhibitors that function by non-selective oxidation. We also discuss the utility of using "open" PTP structures to identify active-site directed compounds, a rather unconventional choice for virtual screening. When integrated closely, virtual and biochemical screening can be used in a productive workflow to identify small molecules targeting PTPs.

Structural basis and targeting of the interaction between fibroblast growth factor-inducible 14 and tumor necrosis factor-like weak inducer of apoptosis.

Deregulation of the TNF-like weak inducer of apoptosis (TWEAK)-fibroblast growth factor-inducible 14 (Fn14) signaling pathway is observed in many diseases, including inflammation, autoimmune diseases, and cancer. Activation of Fn14 signaling by TWEAK binding triggers cell invasion and survival and therefore represents an attractive pathway for therapeutic intervention. Based on structural studies of the TWEAK-binding cysteine-rich domain of Fn14, several homology models of TWEAK were built to investigate plausible modes of TWEAK-Fn14 interaction. Two promising models, centered on different anchoring residues of TWEAK (tyrosine 176 and tryptophan 231), were prioritized using a data-driven strategy. Site-directed mutagenesis of TWEAK at Tyr(176), but not Trp(231), resulted in the loss of TWEAK binding to Fn14 substantiating Tyr(176) as the anchoring residue. Importantly, mutation of TWEAK at Tyr(176) did not disrupt TWEAK trimerization but failed to induce Fn14-mediated nuclear factor κ-light chain enhancer of activated B cell (NF-κB) signaling. The validated structural models were utilized in a virtual screen to design a targeted library of small molecules predicted to disrupt the TWEAK-Fn14 interaction. 129 small molecules were screened iteratively, with identification of molecules producing up to 37% inhibition of TWEAK-Fn14 binding. In summary, we present a data-driven in silico study revealing key structural elements of the TWEAK-Fn14 interaction, followed by experimental validation, serving as a guide for the design of small molecule inhibitors of the TWEAK-Fn14 ligand-receptor interaction. Our results validate the TWEAK-Fn14 interaction as a chemically tractable target and provide the foundation for further exploration utilizing chemical biology approaches focusing on validating this system as a therapeutic target in invasive cancers.

Identification of small molecule inhibitors of PTPσ through an integrative virtual and biochemical approach.

PTPσ is a dual-domain receptor type protein tyrosine phosphatase (PTP) with physiologically important functions which render this enzyme an attractive biological target. Specifically, loss of PTPσ has been shown to elicit a number of cellular phenotypes including enhanced nerve regeneration following spinal cord injury (SCI), chemoresistance in cultured cancer cells, and hyperactive autophagy, a process critical to cell survival and the clearance of pathological aggregates in neurodegenerative diseases. Owing to these functions, modulation of PTPσ may provide therapeutic value in a variety of contexts. Furthermore, a small molecule inhibitor would provide utility in discerning the cellular functions and substrates of PTPσ. To develop such molecules, we combined in silico modeling with in vitro phosphatase assays to identify compounds which effectively inhibit the enzymatic activity of PTPσ. Importantly, we observed that PTPσ inhibition was frequently mediated by oxidative species generated by compounds in solution, and we further optimized screening conditions to eliminate this effect. We identified a compound that inhibits PTPσ with an IC(50) of 10 µM in a manner that is primarily oxidation-independent. This compound favorably binds the D1 active site of PTPσ in silico, suggesting it functions as a competitive inhibitor. This compound will serve as a scaffold structure for future studies designed to build selectivity for PTPσ over related PTPs.

Refinement of the pharmacophore of an agonist ligand of the secretin receptor using conformationally constrained cyclic hexapeptides.

There is a compelling need for the development of small molecule agonists acting at family B G protein-coupled receptors. A possible lead for the development of such drugs was reported when it was recognized that sequences endogenous to the amino terminus of the secretin receptor and certain other receptors in this family possess weak full agonist activity (Dong et al. Mol Pharmacol 2006;70:206-213). In the current report, we extended those observations by building the active dipeptide motif found in the secretin receptor (WD) into each position around a conformationally constrained d-amino acid-containing cyclic hexapeptide, and determining the biological activity of each peptide at the secretin receptor. Indeed, only two positions for WD around this constrained ring resulted in biological activity at the receptor, providing further insights into the structural specificity of this phenomenon. Molecular modeling supported the presence of a unique WD backbone conformation shared only by these active peptides, and provided a more constrained template for future receptor-active agonist drug development.

Bhageerath: an energy based web enabled computer software suite for limiting the search space of tertiary structures of small globular proteins.

We describe here an energy based computer software suite for narrowing down the search space of tertiary structures of small globular proteins. The protocol comprises eight different computational modules that form an automated pipeline. It combines physics based potentials with biophysical filters to arrive at 10 plausible candidate structures starting from sequence and secondary structure information. The methodology has been validated here on 50 small globular proteins consisting of 2-3 helices and strands with known tertiary structures. For each of these proteins, a structure within 3-6 A RMSD (root mean square deviation) of the native has been obtained in the 10 lowest energy structures. The protocol has been web enabled and is accessible at http://www.scfbio-iitd.res.in/bhageerath.

Protein structure evaluation using an all-atom energy based empirical scoring function.

Arriving at the native conformation of a polypeptide chain characterized by minimum most free energy is a problem of long standing interest in protein structure prediction endeavors. Owing to the computational requirements in developing free energy estimates, scoring functions--energy based or statistical--have received considerable renewed attention in recent years for distinguishing native structures of proteins from non-native like structures. Several cleverly designed decoy sets, CASP (Critical Assessment of Techniques for Protein Structure Prediction) structures and homology based internet accessible three dimensional model builders are now available for validating the scoring functions. We describe here an all-atom energy based empirical scoring function and examine its performance on a wide series of publicly available decoys. Barring two protein sequences where native structure is ranked second and seventh, native is identified as the lowest energy structure in 67 protein sequences from among 61,659 decoys belonging to 12 different decoy sets. We further illustrate a potential application of the scoring function in bracketing native-like structures of two small mixed alpha/beta globular proteins starting from sequence and secondary structural information. The scoring function has been web enabled at www.scfbio-iitd.res.in/utility/proteomics/energy.jsp.

A computational pathway for bracketing native-like structures fo small alpha helical globular proteins.

Impressive advances in the applications of bioinformatics for protein structure prediction coupled with growing structural databases on one hand and the insurmountable time-scale problem with ab initio computational methods on the other continue to raise doubts whether a computational solution to the protein folding problem--categorized as an NP-hard problem--is within reach in the near future. Combining some specially designed biophysical filters and vector algebra tools with ab initio methods, we present here a promising computational pathway for bracketing native-like structures of small alpha helical globular proteins departing from secondary structural information. The automated protocol is initiated by generating multiple structures around the loops between secondary structural elements. A set of knowledge-based biophysical filters namely persistence length and radius of gyration, developed and calibrated on approximately 1000 globular proteins, is introduced to screen the trial structures to filter out improbable candidates for the native and reduce the size of the library of probable structures. The ensemble so generated encompasses a few structures with native-like topology. Monte Carlo optimizations of the loop dihedrals are then carried out to remove steric clashes. The resultant structures are energy minimized and ranked according to a scoring function tested previously on a series of decoy sets vis-a-vis their corresponding natives. We find that the 100 lowest energy structures culled from the ensemble of energy optimized trial structures comprise at least a few to within 3-5 angstroms of the native. Thus the formidable "needle in a haystack" problem is narrowed down to finding an optimal solution amongst a computationally tractable number of alternatives. Encouraging results obtained on twelve small alpha helical globular proteins with the above outlined pathway are presented and discussed.