Phenotype screens of murine pancreatic cancer identify a Tgf-α-Ccl2-paxillin axis driving human-like neural invasion

Solid cancers like pancreatic ductal adenocarcinoma (PDAC), a type of pancreatic cancer, frequently exploit nerves for rapid dissemination. This neural invasion (NI) is an independent prognostic factor in PDAC, but insufficiently modeled in genetically engineered mouse models (GEMM) of PDAC. Here, we systematically screened for human-like NI in Europe's largest repository of GEMM of PDAC, comprising 295 different genotypes. This phenotype screen uncovered 2 GEMMs of PDAC with human-like NI, which are both characterized by pancreas-specific overexpression of transforming growth factor α (TGF-α) and conditional depletion of p53. Mechanistically, cancer-cell-derived TGF-α upregulated CCL2 secretion from sensory neurons, which induced hyperphosphorylation of the cytoskeletal protein paxillin via CCR4 on cancer cells. This activated the cancer migration machinery and filopodia formation toward neurons. Disrupting CCR4 or paxillin activity limited NI and dampened tumor size and tumor innervation. In human PDAC, phospho-paxillin and TGF-α-expression constituted strong prognostic factors. Therefore, we believe that the TGF-α-CCL2-CCR4-p-paxillin axis is a clinically actionable target for constraining NI and tumor progression in PDAC.

Corneal bacterial microbiome in patients with keratoconus using next-generation sequencing-based 16S rRNA gene analysis

PURPOSE

To investigate the corneal bacterial microbiome in patients with keratoconus using next-generation sequencing and develop a new perspective on the pathogenesis of the disease.

METHODS

This prospective observational study included 10 patients with keratoconus who underwent corneal crosslinking procedure and 10 healthy controls who underwent photorefractive keratectomy. Patients included in the study were aged 18 years or older. The demographic and clinical characteristics of participants were recorded. Corneal epithelial samples were collected between March 2021 and June 2021. Isolated bacterial DNA from corneal epithelial samples was analyzed using 16 S ribosomal RNA gene analysis. The relative abundance rates at the phylum and genus levels were calculated. Alpha diversity parameters were assessed.

RESULTS

Eleven phyla and 521 genera of bacteria were identified in all participants. At the phylum level, Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were most abundant in both groups. There were no statistical differences between the two groups except Bacteriodetes (p < 0.05). At the genus level, the relative abundance rates of twenty bacteria were significantly different between keratoconus and healthy corneas (p < 0.05). Aquabacterium was the most abundant genus in patients with keratoconus, while Shigella was the most abundant genus in healthy controls. Alpha diversity parameters were lower in patients with keratoconus, although the difference did not reach statistical significance (p > 0.05).

CONCLUSIONS

Our preliminary study revealed that there are similarities and differences in the corneal microbiome between keratoconus and healthy individuals. Further research is required on the relationship between the abnormal corneal microbiome composition and the pathogenesis of keratoconus.

Computational analysis of missense filamin-A variants, including the novel p.Arg484Gln variant of two brothers with periventricular nodular heterotopia

Background

Periventricular nodular heterotopia (PNH) is a cell migration disorder associated with mutations in Filamin-A (FLNA) gene on chromosome X. Majority of the individuals with PNH-associated FLNA mutations are female whereas liveborn males with FLNA mutations are very rare. Fetal viability of the males seems to depend on the severity of the variant. Splicing or severe truncations presumed loss of function of the protein product, lead to male lethality and only partial-loss-of-function variants are reported in surviving males. Those variants mostly manifest milder clinical phenotypes in females and thus avoid detection of the disease in females.

Methods

We describe a novel p.Arg484Gln variant in the FLNA gene by performing whole exome analysis on the index case, his one affected brother and his healthy non-consanguineous parents. The transmission of PNH from a clinically asymptomatic mother to two sons is reported in a fully penetrant classical X-linked dominant mode. The variant was verified via Sanger sequencing. Additionally, we investigated the impact of missense mutations reported in affected males on the FLNa protein structure, dynamics and interactions by performing molecular dynamics (MD) simulations to examine the disease etiology and possible compensative mechanisms allowing survival of the males.

Results

We observed that p.Arg484Gln disrupts the FLNa by altering its structural and dynamical properties including the flexibility of certain regions, interactions within the protein, and conformational landscape of FLNa. However, these impacts existed for only a part the MD trajectories and highly similar patterns observed in the other 12 mutations reported in the liveborn males validated this mechanism.

Conclusion

It is concluded that the variants seen in the liveborn males result in transient pathogenic effects, rather than persistent impairments. By this way, the protein could retain its function occasionally and results in the survival of the males besides causing the disease.

Structural analysis of M1AP variants associated with severely impaired spermatogenesis causing male infertility

Background

Impaired meiosis can result in absence of sperm in the seminal fluid. This condition, namely non-obstructive azoospermia (NOA), is one of the reasons of male infertility. Despite the low number of studies on meiosis 1-associated protein (M1AP) in the literature, M1AP is known to be crucial for spermatogenesis. Recently, seven variants (five missense, one frameshift, one splice-site) have been reported in the M1AP gene as associated with NOA, cryptozoospermia and oligozoospermia in two separate studies. However, all missense variants were evaluated as variant of uncertain significance by these studies. Therefore, we aimed to analyze their structural impacts on the M1AP protein that could lead to NOA.

Methods

We firstly performed an evolutionary conservation analysis for the variant positions. Afterwards, a comprehensive molecular modelling study was performed for the M1AP structure. By utilizing this model, protein dynamics were sampled for the wild-type and variants by performing molecular dynamics (MD) simulations.

Results

All variant positions are highly conserved, indicating that they are potentially important for function. In MD simulations, none of the variants led to a general misfolding or loss of stability in the protein structure, but they did cause severe modifications in the conformational dynamics of M1AP, particularly through changes in local interactions affecting flexibility, hinge and secondary structure.

Conclusions

Due to critical perturbations in protein dynamics, we propose that these variants may cause NOA by affecting important interactions regulating meiosis, particularly in wild-type M1AP deficiency since the variants are reported to be homozygous or bi-allelic in the infertile individuals. Our results provided reasonable insights about the M1AP structure and the effects of the variants to the structure and dynamics, which should be further investigated by experimental studies to validate.

Is cutaneous microbiota a player in disease pathogenesis? Comparison of cutaneous microbiota in psoriasis and seborrheic dermatitis with scalp involvement

BACKGROUND

Knowledge about cutaneous microbiota in psoriasis vulgaris and seborrheic dermatitis is limited, and a comparison of microbiota in the two diseases was not yet previously undertaken.

AIMS/OBJECTIVES

This study aimed to compare the scalp lesional and non-lesional microbiota in psoriasis vulgaris and seborrheic dermatitis with that in a healthy control group.

METHODS

Fifty samples were taken with sterile swabs from patients' and controls' scalps, and 16S rRNA gene sequencing analyses were performed.

RESULTS

Alpha and beta diversity analyses showed that bacterial load and diversity were significantly increased in psoriasis vulgaris and seborrheic dermatitis lesions compared to the controls. As phyla, Actinobacteria decreased and Firmicutes increased, while as genera, Propionibacterium decreased; Staphylococcus, Streptococcus, Aquabacterium, Neisseria and Azospirillum increased in lesions of both diseases. Specifically, Mycobacterium, Finegoldia, Haemophilus and Ezakiella increased in psoriasis vulgaris and Enhydrobacter, Micromonospora and Leptotrichia increased in seborrheic dermatitis lesions. Mycobacterium, Ezakiella and Peptoniphilus density were higher in psoriasis vulgaris compared to seborrheic dermatitis lesions. The bacterial diversity and load values of non-lesional scalp in psoriasis vulgaris and seborrheic dermatitis lay between those of lesional areas and controls.

LIMITATIONS

The small sample size is the main limitation of this study.

CONCLUSION

Higher bacterial diversity was detected in lesions of both psoriasis and seborrheic dermatitis compared to the controls, but similar alterations were observed when the two diseases were compared. Although these differences could be a result rather than a cause of the two diseases, there is a need to analyze all members of the microbiota and microbiota-host interactions.

Investigation of multiple sclerosis-related pathways through the integration of genomic and proteomic data

Background

Multiple sclerosis (MS) has a complex pathophysiology, variable clinical presentation, and unpredictable prognosis; understanding the underlying mechanisms requires combinatorial approaches that warrant the integration of diverse molecular omics data.

Methods

Here, we combined genomic and proteomic data of the same individuals among a Turkish MS patient group to search for biologically important networks. We previously identified differentially-expressed proteins by cerebrospinal fluid proteome analysis of 179 MS patients and 42 non-MS controls. Among this study group, 11 unrelated MS patients and 60 independent, healthy controls were subjected to whole-genome SNP genotyping, and genome-wide associations were assessed. Pathway enrichment analyses of MS-associated SNPs and differentially-expressed proteins were conducted using the functional enrichment tool, PANOGA.

Results

Nine shared pathways were detected between the genomic and proteomic datasets after merging and clustering the enriched pathways. Complement and coagulation cascade was the most significantly associated pathway (hsa04610, P = 6.96 × 10−30). Other pathways involved in neurological or immunological mechanisms included adherens junctions (hsa04520, P = 6.64 × 10−25), pathogenic Escherichia coli infection (hsa05130, P = 9.03 × 10−14), prion diseases (hsa05020, P = 5.13 × 10−13).

Conclusion

We conclude that integrating multiple datasets of the same patients helps reducing false negative and positive results of genome-wide SNP associations and highlights the most prominent cellular players among the complex pathophysiological mechanisms.

Identifying and elucidating the roles of Y198N and Y204F mutations in the PAH enzyme through molecular dynamic simulations

Phenylketonuria is an autosomal recessive disorder caused by mutations in the phenylalanine hydroxylase gene. In phenylketonuria causes various symptoms including severe mental retardation. PAH gene of a classical Phenylketonuria patient was sequenced, and two novel heterozygous mutations, p.Y198N and p.Y204F, were found. This study aimed to reveal the impacts of these variants on the structural stability of the PAH enzyme. In-silico analyses using prediction tools and molecular dynamics simulations were performed. Mutations were introduced to the wild type catalytic monomer and full length tetramer crystal structures. Variant pathogenicity analyses predicted p.Y198N to be damaging, and p.Y204F to be benign by some prediction tools and damaging by others. Simulations suggested p.Y198N mutation cause significant fluctuations in the spatial organization of two catalytic residues in the temperature accelerated MD simulations with the monomer and increased root-mean-square deviations in the tetramer structure. p.Y204F causes noticeable changes in the spatial positioning of T278 suggesting a possible segregation from the catalytic site in temperature accelerated MD simulations with the monomer. This mutation also leads to increased root-mean-square fluctuations in the regulatory domain which may lead to conformational change resulting in inhibition of dimerization and enzyme activation. Our study reports two novel mutations in the PAH gene and gives insight to their effects on the PAH activity. MD simulations did not yield conclusive results that explains the phenotype but gave plausible insight to possible effects which should be investigated further with in-silico and in-vitro studies to assess the roles of these mutations in etiology of PKU. Communicated by Ramaswamy H. Sarma.

CogNet: classification of gene expression data based on ranked active-subnetwork-oriented KEGG pathway enrichment analysis

Most of the traditional gene selection approaches are borrowed from other fields such as statistics and computer science, However, they do not prioritize biologically relevant genes since the ultimate goal is to determine features that optimize model performance metrics not to build a biologically meaningful model. Therefore, there is an imminent need for new computational tools that integrate the biological knowledge about the data in the process of gene selection and machine learning. Integrative gene selection enables incorporation of biological domain knowledge from external biological resources. In this study, we propose a new computational approach named CogNet that is an integrative gene selection tool that exploits biological knowledge for grouping the genes for the computational modeling tasks of ranking and classification. In CogNet, the pathfindR serves as the biological grouping tool to allow the main algorithm to rank active-subnetwork-oriented KEGG pathway enrichment analysis results to build a biologically relevant model. CogNet provides a list of significant KEGG pathways that can classify the data with a very high accuracy. The list also provides the genes belonging to these pathways that are differentially expressed that are used as features in the classification problem. The list facilitates deep analysis and better interpretability of the role of KEGG pathways in classification of the data thus better establishing the biological relevance of these differentially expressed genes. Even though the main aim of our study is not to improve the accuracy of any existing tool, the performance of the CogNet outperforms a similar approach called maTE while obtaining similar performance compared to other similar tools including SVM-RCE. CogNet was tested on 13 gene expression datasets concerning a variety of diseases.

SARS-CoV-2 isolation and propagation from Turkish COVID-19 patients

The novel coronavirus pneumonia, which was named later as coronavirus disease 2019 (COVID-19), is caused by the severe acute respiratory syndrome coronavirus 2, namely SARS-CoV-2. It is a positive-strand RNA virus that is the seventh coronavirus known to infect humans. The COVID-19 outbreak presents enormous challenges for global health behind the pandemic outbreak. The first diagnosed patient in Turkey has been reported by the Republic of Turkey Ministry of Health on March 11, 2020. In May, over 150,000 cases in Turkey, and 5.5 million cases around the world have been declared. Due to the urgent need for a vaccine and antiviral drug, isolation of the virus is crucial. Here, we report 1 of the first isolation and characterization studies of SARS-CoV-2 from nasopharyngeal and oropharyngeal specimens of diagnosed patients in Turkey. This study provides an isolation and replication methodology,and cell culture tropism of the virus that will be available to the research communities.

Understanding thermal and organic solvent stability of thermoalkalophilic lipases: insights from computational predictions and experiments

Bacillus thermocatenulatus lipase (BTL2), a member of the isolated lipase family known as thermoalkalophilic lipases, carries potential for industrial applications owing to its ability to catalyze versatile reactions under extreme conditions. This study investigates the molecular effects of distinct solvents on the stability of BTL2 at different temperatures, aiming to contribute to lipase use in industrial applications. Initially, molecular dynamic (MD) simulations were carried out to address for the molecular impacts of distinct solvents on the structural stability of BTL2 at different temperatures. Two lipase conformations representing the active and inactive forms were simulated in 5 solvents including water, ethanol, methanol, cyclohexane, and toluene. Low temperature simulations showed that polar solvents led to enhanced lid fluctuations compared with non-polar solvents reflecting a more dynamic equilibrium between active and inactive lipase conformations in polar solvents including water, while the overall structure of the lipase in both forms became more rigid in non-polar solvents than they were in polar solvent. Notably, the native lipase fold was maintained in non-polar solvents even at high temperatures, indicating an enhancement of lipase's thermostability in non-polar organic solvents. Next, we conducted experiments for which BTL2 was expressed in a heterologous host and purified to homogeneity, and its thermostability in different solvents was assessed. Parallel to the computational findings, experimental results suggested that non-polar organic solvents contributed to BTL2's thermostability at concentrations as high as 70% (v/v). Altogether, this study provides beneficial insights to the lipase use under extreme conditions. Graphical Abstract.

Adaptive phenotypic modulations lead to therapy resistance in chronic myeloid leukemia cells

Tyrosine kinase inhibitor (TKI) resistance is a major problem in chronic myeloid leukemia (CML). We generated a TKI-resistant K562 sub-population, K562-IR, under selective imatinib-mesylate pressure. K562-IR cells are CD34-/CD38-, BCR-Abl-independent, proliferate slowly, highly adherent and form intact tumor spheroids. Loss of CD45 and other hematopoietic markers reveal these cells have diverged from their hematopoietic origin. CD34 negativity, high expression of E-cadherin and CD44; decreased levels of CD45 and β-catenin do not fully confer with the leukemic stem cell (LSC) phenotype. Expression analyses reveal that K562-IR cells differentially express tissue/organ development and differentiation genes. Our data suggest that the observed phenotypic shift is an adaptive process rendering cells under TKI stress to become oncogene independent. Cells develop transcriptional instability in search for a gene expression framework suitable for new environmental stresses, resulting in an adaptive phenotypic shift in which some cells partially display LSC-like properties. With leukemic/cancer stem cell targeted therapies underway, the difference between treating an entity and a spectrum of dynamic cellular states will have conclusive effects on the outcome.

A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

Background

Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics.

Results

In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer.

Conclusion

While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as; endocytosis, apoptosis, glutamatergic synapse, MAPK, ErbB, TGF-beta and Toll-like receptor pathways. Overall, in addition to novel analysis framework, our study reveals important thyroid-cancer related mechanisms, secondary molecular alterations and contributes to better knowledge of thyroid cancer aetiology.

Identifying SNP targeted pathways in partial epilepsies with genome-wide association study data

PURPOSE

In a recent genome-wide association study for partial epilepsies in the European population, a common genetic variation has been reported to affect partial epilepsy only modestly. However, in complex diseases such as partial epilepsy, multiple factors (e.g. single nucleotide polymorphisms, microRNAs, metabolic and epigenetic factors) may target different sets of genes in the same pathway, affecting its function and thus causing the disease development. In this regard, we hypothesize that the pathways are critical for elucidating the mechanisms underlying partial epilepsy.

METHODS

Previously we had developed a novel methodology with the aim of identifying the disease-related pathways. We had combined evidence of genetic association with current knowledge of (i) biochemical pathways, (ii) protein-protein interaction networks, and (iii) the functional information of selected single nucleotide polymorphisms. In our present study, we apply this methodology to a data set on partial epilepsy, including 3445 cases and 6935 controls of European ancestry.

RESULTS

We have identified 30 overrepresented pathways with corrected p-values smaller than 10(-12). These pathways include complement and coagulation cascades, cell cycle, focal adhesion, extra cellular matrix-receptor interaction, JAK-STAT signaling pathway, MAPK signaling pathway, proteasome, ribosome, calcium signaling and regulation of actin cytoskeleton pathways. Most of these pathways have growing scientific support in the literature as being associated with partial epilepsy. We also demonstrate that different factors affect distinct parts of the pathways, as shown here on complement and coagulation cascades pathway with a comparison of gene expression vs. genome-wide association study.

CONCLUSIONS

Traditional studies on genome-wide association have not revealed strong associations in epilepsies, since these single nucleotide polymorphisms are not shared by most of the patients. Our results suggest that it is more effective to incorporate the functional effect of a single nucleotide polymorphism on the gene product, protein-protein interaction networks and functional enrichment tools into genome-wide association studies. These can then be used to determine leading molecular pathways, which cannot be detected through traditional analyses. We hope that this type of analysis brings the research community one step closer to unraveling the complex genetic structure of epilepsies.

Prediction of peptides binding to MHC class I and II alleles by temporal motif mining

BACKGROUND

MHC (Major Histocompatibility Complex) is a key player in the immune response of most vertebrates. The computational prediction of whether a given antigenic peptide will bind to a specific MHC allele is important in the development of vaccines for emerging pathogens, the creation of possibilities for controlling immune response, and for the applications of immunotherapy. One of the problems that make this computational prediction difficult is the detection of the binding core region in peptides, coupled with the presence of bulges and loops causing variations in the total sequence length. Most machine learning methods require the sequences to be of the same length to successfully discover the binding motifs, ignoring the length variance in both motif mining and prediction steps. In order to overcome this limitation, we propose the use of time-based motif mining methods that work position-independently.

RESULTS

The prediction method was tested on a benchmark set of 28 different alleles for MHC class I and 27 different alleles for MHC class II. The obtained results are comparable to the state of the art methods for both MHC classes, surpassing the published results for some alleles. The average prediction AUC values are 0.897 for class I, and 0.858 for class II.

CONCLUSIONS

Temporal motif mining using partial periodic patterns can capture information about the sequences well enough to predict the binding of the peptides and is comparable to state of the art methods in the literature. Unlike neural networks or matrix based predictors, our proposed method does not depend on peptide length and can work with both short and long fragments. This advantage allows better use of the available training data and the prediction of peptides of uncommon lengths.

Necessary conditions for avoiding incorrect polypeptide folds in conformational search by energy minimization

Low energy conformations have been generated for melittin, pancreatic polypeptide, and ribonuclease S-peptide, both in the vicinity of x-ray structures by energy refinement and by an unconstrained search over the entire conformational space. Since the structural polymorphism of these medium-sized peptides in crystal and solution is moderate, comparing the calculated conformation to x-ray and nmr data provides information on local and global behavior of potential functions. Local analysis includes standardization calculations, which show that models with standard geometry can approximate good resolution x-ray data with less than 0.5 A rms deviation (RMSD). However, the atomic coordinates are shifted up to 2 A RMSD by local energy minimization, and thus 2 A is generally the smallest RMSD value one can target in a conformational search using the same energy evaluation models. The unconstrained search was performed by a buildup-type method based on dynamic programming. To accelerate the generation of structures in the conformational search, we used the ECEPP potential, defined in terms of standard polypeptide geometry. A number of low energy conformations were further refined by relaxing the assumption of standard bond lengths and bond angles through the use of the CHARMM potential, and the hydrophobic folding energies of Eisenberg and McLachlan were calculated. Each conformation is described in terms of the RMSD from the native, hydrogen-bonding structure, solvent-accessible surface area, and the ratio of surfaces corresponding to nonpolar and polar residues. The unconstrained search finds conformations that are different from the native, sometimes substantially, and in addition, have lower conformational energies than the native. The origin of deviations is different for each of the three peptides, but in all examples the refined x-ray structures have lower energies than the calculated incorrect folds when (1) the assumption of standard bond lengths and bond angles is relaxed; (2) a small and constant effective dielectric permittivity (epsilon < 10) is used; and (3) the hydrophobic folding energy is incorporated into the potential.