Antimicrobial glycoprotein 2 (GP2) in gallstones, bile fluid and peribiliary glands of patients with primary sclerosing cholangitis.

BACKGROUND: Glycoprotein-2 (GP2) IgA is a predictor of disease severity in primary sclerosing cholangitis (PSC). We examined GP2's occurrence in the biliary tract, the site of inflammation. METHODS: GP2 was analyzed using ELISA, immunoblotting, mass spectrometry, and immunohistochemistry. The samples included: 20 bile and 30 serum samples from PSC patients, 23 bile and 11 serum samples from patients with gallstone disease (GD), 15 bile samples from healthy individuals undergoing liver-donation surgery (HILD), 20 extracts of gallstones (GE) obtained during cholecystectomy, and 101 blood-donor sera. RESULTS: Biliary GP2 concentrations were significantly higher in patients with PSC and GD than in HILD (p < 0.0001). Serum GP2 levels were similar in PSC and GD patients, and controls, but lower than in bile (p < 0.0001). GP2 was detected in all 20 GEs. Mass spectrometry identified GP2 in the bile of 2 randomly selected GD and 2 PSC patients, and in none of 2 HILD samples. GP2 was found in peribiliary glands in 8 out of 12 PSC patients, showing morphological changes in acinar cells, but not in GD-gallbladders. CONCLUSIONS: GP2 is present in bile of PSC and GD patients. It is synthesized in the peribiliary glands of PSC patients, supporting a pathogenic role for biliary GP2 in PSC.

MicroRNA biomarkers as next-generation diagnostic tools for neurodegenerative diseases: a comprehensive review.

Neurodegenerative diseases (NDs) are characterized by abnormalities within neurons of the brain or spinal cord that gradually lose function, eventually leading to cell death. Upon examination of affected tissue, pathological changes reveal a loss of synapses, misfolded proteins, and activation of immune cells-all indicative of disease progression-before severe clinical symptoms become apparent. Early detection of NDs is crucial for potentially administering targeted medications that may delay disease advancement. Given their complex pathophysiological features and diverse clinical symptoms, there is a pressing need for sensitive and effective diagnostic methods for NDs. Biomarkers such as microRNAs (miRNAs) have been identified as potential tools for detecting these diseases. We explore the pivotal role of miRNAs in the context of NDs, focusing on Alzheimer's disease, Parkinson's disease, Multiple sclerosis, Huntington's disease, and Amyotrophic Lateral Sclerosis. The review delves into the intricate relationship between aging and NDs, highlighting structural and functional alterations in the aging brain and their implications for disease development. It elucidates how miRNAs and RNA-binding proteins are implicated in the pathogenesis of NDs and underscores the importance of investigating their expression and function in aging. Significantly, miRNAs exert substantial influence on post-translational modifications (PTMs), impacting not just the nervous system but a wide array of tissues and cell types as well. Specific miRNAs have been found to target proteins involved in ubiquitination or de-ubiquitination processes, which play a significant role in regulating protein function and stability. We discuss the link between miRNA, PTM, and NDs. Additionally, the review discusses the significance of miRNAs as biomarkers for early disease detection, offering insights into diagnostic strategies.

Challenges and opportunities in processing NanoString nCounter data.

NanoString nCounter is a medium-throughput technology used in mRNA and miRNA differential expression studies. It offers several advantages, including the absence of an amplification step and the ability to analyze low-grade samples. Despite its considerable strengths, the popularity of the nCounter platform in experimental research stabilized in 2022 and 2023, and this trend may continue in the upcoming years. Such stagnation could potentially be attributed to the absence of a standardized analytical pipeline or the indication of optimal processing methods for nCounter data analysis. To standardize the description of the nCounter data analysis workflow, we divided it into five distinct steps: data pre-processing, quality control, background correction, normalization and differential expression analysis. Next, we evaluated eleven R packages dedicated to nCounter data processing to point out functionalities belonging to these steps and provide comments on their applications in studies of mRNA and miRNA samples.

Natural phenolic compounds as biofilm inhibitors of multidrug-resistant Escherichia coli - the role of similar biological processes despite structural diversity.

Multidrug-resistant gram-negative pathogens such as Escherichia coli have become increasingly difficult to treat and therefore alternative treatment options are needed. Targeting virulence factors like biofilm formation could be one such option. Inhibition of biofilm-related structures like curli and cellulose formation in E. coli has been shown for different phenolic natural compounds like epigallocatechin gallate. This study demonstrates this effect for other structurally unrelated phenolics, namely octyl gallate, scutellarein and wedelolactone. To verify whether these structurally different compounds influence identical pathways of biofilm formation in E. coli a broad comparative RNA-sequencing approach was chosen with additional RT-qPCR to gain initial insights into the pathways affected at the transcriptomic level. Bioinformatical analysis of the RNA-Seq data was performed using DESeq2, BioCyc and KEGG Mapper. The comparative bioinformatics analysis on the pathways revealed that, irrespective of their structure, all compounds mainly influenced similar biological processes. These pathways included bacterial motility, chemotaxis, biofilm formation as well as metabolic processes like arginine biosynthesis and tricarboxylic acid cycle. Overall, this work provides the first insights into the potential mechanisms of action of novel phenolic biofilm inhibitors and highlights the complex regulatory processes of biofilm formation in E. coli.

Over-Expression of LEDGF/p75 in HEp-2 Cells Enhances Autoimmune IgG Response in Patients with Benign Prostatic Hyperplasia-A Novel Diagnostic Approach with Therapeutic Consequence?

Lens epithelium-derived growth factor splice variant of 75 kDa (LEDGF/p75) is an autoantigen over-expressed in solid tumors and acts as a stress-related transcriptional co-activator. Participation of autoimmune responses in the pathophysiology of benign prostatic hyperplasia (PBH) and a corresponding immunosuppressive therapy by TNFalpha antagonists has been recently suggested. Thus, autoAb testing could aid in the diagnosis of BPH patients profiting from such therapy. We generated CRISPR/Cas9 modified HEp-2 LEDGF knock-out (KO) and HEp-2 LEDGF/p75 over-expressing (OE) cells and examined IgG autoantibody reactivity to LEDGF/p75 in patients with prostate cancer (PCa, n = 89), bladder cancer (BCa, n = 116), benign prostatic hyperplasia (BPH, n = 103), and blood donors (BD, n = 60) by indirect immunofluorescence assay (IFA). Surprisingly, we could not detect elevated binding of autoAbs against LEDGF/p75 in cancer patients, but autoAb reactivity to LEDGF/p75 OE cells in about 50% of patients with BPH was unexpectedly significantly increased. Furthermore, a line immunoassay enabling the detection of 18 different autoAbs revealed a significantly increased occurrence of anti-dsDNA autoAbs in 34% of BPH patients in contrast to tumor patients and BD. This finding was confirmed by anti-mitochondrial (mDNA) autoAb detection with the Crithidia luciliae immunofluorescence test, which also showed a significantly higher prevalence (34%) of anti-mDNA autoAbs in BPH. In summary, our study provided further evidence for the occurrence of autoimmune responses in BPH. Furthermore, LEDGF/p75 over-expression renders HEp-2 cells more autoantigenic and an ideal target for autoAb analysis in BPH with a potential therapy consequence.

Human glycoprotein-2 expressed in Brunner glands - A putative autoimmune target and link between Crohn's and coeliac disease.

Glycoprotein 2 (GP2) is an autoantigen in Crohn's (CD) and coeliac disease (CeD). We assessed GP2-isoform (GP21-4)-expression in intestinal biopsies of paediatric patients with CD, CeD, ulcerative colitis (UC), and healthy children (HC). Transcription of GP21-4 was elevated in proximal small intestine in CeD and CD patients (only GP22/4) compared to jejunum (CeD/CD) and large bowel (CD). CeD patients demonstrated higher duodenal GP22/4-mRNA levels compared to HC/UC patients whereas CD patients showed higher GP24-mRNA levels compared to UC patients. Duodenal synthesis of only small GP2 isoforms (GP23/4) was demonstrated in epithelial cells in patients/HC and in Brunner glands (also large isoforms) with a more frequent apical location in CD/CeD patients. All four GP2 isoforms interacted with gliadin and phosphopeptidomannan. Gliadin digestion improved binding to GP2 isoforms. GP21-4 binding to CeD/CD-related antigens, elevated duodenal GP21-4-mRNA transcription, and GP2-protein secretion in Brunner glands of CeD/CD patients suggest an autoimmune CeD/CD link.

PR3-ANCAs Detected by Third-Generation ELISA Predicts Severe Disease and Poor Survival in Primary Sclerosing Cholangitis.

A highly sensitive detection of anti-neutrophil cytoplasmic antibodies to serine proteinase-3 (PR3-ANCAs) aids in the serological diagnosis of autoimmune liver disorders and the prediction of severity in primary sclerosing cholangitis (PSC). Here, we evaluate a novel third-generation ELISA for the detection of PR3-ANCAs. In total, 309 patients with PSC, 51 with primary biliary cholangitis (PBC), and 120 healthy blood donors (BD) were analyzed. For the survival analysis in PSC, the outcome was defined as liver-transplantation-free survival during the follow-up. Positive PR3-ANCA levels were found in 74/309 (24.0%) of patients with PSC. No BDs and one patient with PBC demonstrated PR3-ANCA positivity. PR3-ANCAs were revealed as independent predictors for a poor PSC outcome (study endpoint: liver transplantation/death, log-rank test, p = 0.02). PR3-ANCA positivity, lower albumin levels, and higher bilirubin concentrations were independent risks of a poor survival (Cox proportional-hazards regression analysis, p < 0.05). The Mayo risk score for PSC was associated with PR3-ANCA positivity (p = 0.01) and the disease severity assessed with a model of end-stage liver disease (MELD) and extended MELD-Na (p < 0.05). PR3-ANCAs detected by a third-generation ELISA are diagnostic and prognostic markers for PSC. Their wider use could help to identify patients who are at-risk of a more severe disease.

Profiling and imaging of forensic evidence - A pan-European forensic round robin study part 1: Document forgery.

The forensic scenario, on which the round robin study was based, simulated a suspected intentional manipulation of a real estate rental agreement consisting of a total of three pages. The aims of this study were to (i) establish the amount and reliability of information extractable from a single type of evidence and to (ii) provide suggestions on the most suitable combination of compatible techniques for a multi-modal imaging approach to forgery detection. To address these aims, seventeen laboratories from sixteen countries were invited to answer the following tasks questions: (i) which printing technique was used? (ii) were the three pages printed with the same printer? (iii) were the three pages made from the same paper? (iv) were the three pages originally stapled? (v) were the headings and signatures written with the same ink? and (vi) were headings and signatures of the same age on all pages? The methods used were classified into the following categories: Optical spectroscopy, including multispectral imaging, smartphone mapping, UV-luminescence and LIBS; Infrared spectroscopy, including Raman and FTIR (micro-)spectroscopy; X-ray spectroscopy, including SEM-EDX, PIXE and XPS; Mass spectrometry, including ICPMS, SIMS, MALDI and LDIMS; Electrostatic imaging, as well as non-imaging methods, such as non-multimodal visual inspection, (micro-)spectroscopy, physical testing and thin layer chromatography. The performance of the techniques was evaluated as the proportion of discriminated sample pairs to all possible sample pairs. For the undiscriminated sample pairs, a distinction was made between undecidability and false positive claims. It was found that none of the methods used were able to solve all tasks completely and/or correctly and that certain methods were a priori judged unsuitable by the laboratories for some tasks. Correct results were generally achieved for the discrimination of printer toners, whereas incorrect results in the discrimination of inks. For the discrimination of paper, solid state analytical methods proved to be superior to mass spectrometric methods. None of the participating laboratories deemed addressing ink age feasible. It was concluded that correct forensic statements can only be achieved by the complementary application of different methods and that the classical approach of round robin studies to send standardised subsamples to the participants is not feasible for a true multimodal approach if the techniques are not available at one location.

Benchmarks in antimicrobial peptide prediction are biased due to the selection of negative data.

Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target not only microorganisms but also viruses and cancer cells. Due to their lower selection for resistance compared with traditional antibiotics, AMPs have been attracting the ever-growing attention from researchers, including bioinformaticians. Machine learning represents the most cost-effective method for novel AMP discovery and consequently many computational tools for AMP prediction have been recently developed. In this article, we investigate the impact of negative data sampling on model performance and benchmarking. We generated 660 predictive models using 12 machine learning architectures, a single positive data set and 11 negative data sampling methods; the architectures and methods were defined on the basis of published AMP prediction software. Our results clearly indicate that similar training and benchmark data set, i.e. produced by the same or a similar negative data sampling method, positively affect model performance. Consequently, all the benchmark analyses that have been performed for AMP prediction models are significantly biased and, moreover, we do not know which model is the most accurate. To provide researchers with reliable information about the performance of AMP predictors, we also created a web server AMPBenchmark for fair model benchmarking. AMPBenchmark is available at http://BioGenies.info/AMPBenchmark.

Applications of Neural Networks in Biomedical Data Analysis.

Neural networks for deep-learning applications, also called artificial neural networks, are important tools in science and industry. While their widespread use was limited because of inadequate hardware in the past, their popularity increased dramatically starting in the early 2000s when it became possible to train increasingly large and complex networks. Today, deep learning is widely used in biomedicine from image analysis to diagnostics. This also includes special topics, such as forensics. In this review, we discuss the latest networks and how they work, with a focus on the analysis of biomedical data, particularly biomarkers in bioimage data. We provide a summary on numerous technical aspects, such as activation functions and frameworks. We also present a data analysis of publications about neural networks to provide a quantitative insight into the use of network types and the number of journals per year to determine the usage in different scientific fields.

Novel Anti Double-Stranded Nucleic Acids Full-Length Recombinant Camelid Heavy-Chain Antibody for the Detection of miRNA.

The discovery that certain diseases have specific miRNA signatures which correspond to disease progression opens a new biomarker category. The detection of these small non-coding RNAs is performed routinely using body fluids or tissues with real-time PCR, next-generation sequencing, or amplification-based miRNA assays. Antibody-based detection systems allow an easy onset handling compared to PCR or sequencing and can be considered as alternative methods to support miRNA diagnostic in the future. In this study, we describe the generation of a camelid heavy-chain-only antibody specifically recognizing miRNAs to establish an antibody-based detection method. The generation of nucleic acid-specific binders is a challenge. We selected camelid binders via phage display, expressed them as VHH as well as full-length antibodies, and characterized the binding to several miRNAs from a signature specific for dilated cardiomyopathy. The described workflow can be used to create miRNA-specific binders and establish antibody-based detection methods to provide an additional way to analyze disease-specific miRNA signatures.

Genotyping of familial Mediterranean fever gene (MEFV)-Single nucleotide polymorphism-Comparison of Nanopore with conventional Sanger sequencing.

BACKGROUND: Through continuous innovation and improvement, Nanopore sequencing has become a powerful technology. Because of its fast processing time, low cost, and ability to generate long reads, this sequencing technique would be particularly suitable for clinical diagnostics. However, its raw data accuracy is inferior in contrast to other sequencing technologies. This constraint still results in limited use of Nanopore sequencing in the field of clinical diagnostics and requires further validation and IVD certification. METHODS: We evaluated the performance of latest Nanopore sequencing in combination with a dedicated data-analysis pipeline for single nucleotide polymorphism (SNP) genotyping of the familial Mediterranean fever gene (MEFV) by amplicon sequencing of 47 clinical samples. Mutations in MEFV are associated with Mediterranean fever, a hereditary periodic fever syndrome. Conventional Sanger sequencing, which is commonly applied in clinical genetic diagnostics, was used as a reference method. RESULTS: Nanopore sequencing enabled the sequencing of 10 target regions within MEFV with high read depth (median read depth 7565x) in all samples and identified a total of 435 SNPs in the whole sample collective, of which 29 were unique. Comparison of both sequencing workflows showed a near perfect agreement with no false negative calls. Precision, Recall, and F1-Score of the Nanopore sequencing workflow were > 0.99, respectively. CONCLUSIONS: These results demonstrated the great potential of current Nanopore sequencing for application in clinical diagnostics, at least for SNP genotyping by amplicon sequencing. Other more complex applications, especially structural variant identification, require further in-depth clinical validation.

A multiparametric fluorescence assay for screening aptamer-protein interactions based on microbeads.

For improving aptamer-ligand binding we have developed a screening system that defines optimal binding buffer composition. Using multiplex assays, one buffer system is needed which guarantees the specific binding of all aptamers. We investigated nine peer-reviewed DNA aptamers. Non-specific binding of aptamers is an obstacle. To address this, we investigated 16 proteins as specificity controls bound covalently to encoded microbeads in a multiplex assay. Increasing the NaCl concentration decreased the binding for all aptamers. Changing pH values by one unit higher or lower did not influence the aptamer binding significantly. However, pH < 5 led to non-specific binding for all aptamers. The PfLDH-aptamer selected in the absence of divalent cations exhibited doubling of its binding signal by the addition of Ca2+ and Mg2+. We confirmed Ca2+ and Mg2+ dependency of the aptamers for streptavidin and thrombin by observing a 90% and 50% binding decrease, respectively. We also achieved a doubling of binding for the streptavidin aptamer when replacing Ca2+ and Mg2+ by Mn2+. A buffer suitable for all aptamers can have considerable variations in pH or ionic strength, but divalent cations (Ca2+, Mg2+, Mn2+) are essential.

Adhesion of Enteropathogenic, Enterotoxigenic, and Commensal Escherichia coli to the Major Zymogen Granule Membrane Glycoprotein 2.

Pathogenic bacteria, such as enteropathogenic Escherichia coli (EPEC) and enterotoxigenic E. coli (ETEC), cause diarrhea in mammals. In particular, E. coli colonizes and infects the gastrointestinal tract via type 1 fimbriae (T1F). Here, the major zymogen granule membrane glycoprotein 2 (GP2) acts as a host cell receptor. GP2 is also secreted by the pancreas and various mucous glands, interacting with luminal type 1 fimbriae-positive E. coli. It is unknown whether GP2 isoforms demonstrate specific E. coli pathotype binding. In this study, we investigated interactions of human, porcine, and bovine EPEC and ETEC, as well as commensal E. coli isolates with human, porcine, and bovine GP2. We first defined pathotype- and host-associated FimH variants. Second, we could prove that GP2 isoforms bound to FimH variants to various degrees. However, the GP2-FimH interactions did not seem to be influenced by the host specificity of E. coli. In contrast, soluble GP2 affected ETEC infection and phagocytosis rates of macrophages. Preincubation of the ETEC pathotype with GP2 reduced the infection of cell lines. Furthermore, preincubation of E. coli with GP2 improved the phagocytosis rate of macrophages. Our findings suggest that GP2 plays a role in the defense against E. coli infection and in the corresponding host immune response. IMPORTANCE Infection by pathogenic bacteria, such as certain Escherichia coli pathotypes, results in diarrhea in mammals. Pathogens, including zoonotic agents, can infect different hosts or show host specificity. There are Escherichia coli strains which are frequently transmitted between humans and animals, whereas other Escherichia coli strains tend to colonize only one host. This host specificity is still not fully understood. We show that glycoprotein 2 is a selective receptor for particular Escherichia coli strains or variants of the adhesin FimH but not a selector for a species-specific Escherichia coli group. We demonstrate that GP2 is involved in the regulation of colonization and infection and thus represents a molecule of interest for the prevention or treatment of disease.

A semi-automated, isolation-free, high-throughput SARS-CoV-2 reverse transcriptase (RT) loop-mediated isothermal amplification (LAMP) test.

Shortages of reverse transcriptase (RT)-polymerase chain reaction (PCR) reagents and related equipment during the COVID-19 pandemic have demonstrated the need for alternative, high-throughput methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-mass screening in clinical diagnostic laboratories. A robust, SARS-CoV-2 RT-loop-mediated isothermal amplification (RT-LAMP) assay with high-throughput and short turnaround times in a clinical laboratory setting was established and compared to two conventional RT-PCR protocols using 323 samples of individuals with suspected SARS-CoV-2 infection. Limit of detection (LoD) and reproducibility of the isolation-free SARS-CoV-2 RT-LAMP test were determined. An almost perfect agreement (Cohen's kappa > 0.8) between the novel test and two classical RT-PCR protocols with no systematic difference (McNemar's test, P > 0.05) was observed. Sensitivity and specificity were in the range of 89.5 to 100% and 96.2 to 100% dependent on the reaction condition and the RT-PCR method used as reference. The isolation-free RT-LAMP assay showed high reproducibility (Tt intra-run coefficient of variation [CV] = 0.4%, Tt inter-run CV = 2.1%) with a LoD of 95 SARS-CoV-2 genome copies per reaction. The established SARS-CoV-2 RT-LAMP assay is a flexible and efficient alternative to conventional RT-PCR protocols, suitable for SARS-CoV-2 mass screening using existing laboratory infrastructure in clinical diagnostic laboratories.

LoopTag FRET Probe System for Multiplex qPCR Detection of Borrelia Species.

BACKGROUND: Laboratory diagnosis of Lyme borreliosis refers to some methods with known limitations. Molecular diagnostics using specific nucleic acid probes may overcome some of these limitations. METHODS: We describe the novel reporter fluorescence real-time polymerase chain reaction (PCR) probe system LoopTag for detection of Borrelia species. Advantages of the LoopTag system include having cheap conventional fluorescence dyes, easy primer design, no restrictions for PCR product lengths, robustness, high sequence specificity, applicability for multiplex real-time PCRs, melting curve analysis (single nucleotide polymorphism analysis) over a large temperature range, high sensitivity, and easy adaptation of conventional PCRs. RESULTS: Using the LoopTag probe system we were able to detect all nine tested European species belonging to the Borrelia burgdorferi (sensu lato) complex and differentiated them from relapsing fever Borrelia species. As few as 10 copies of Borrelia in one PCR reaction were detectable. CONCLUSION: We established a novel multiplex probe real-time PCR system, designated LoopTag, that is simple, robust, and incorporates melting curve analysis for the detection and in the differentiation of European species belonging to the Borrelia burgdorferi s.l. complex.

Fluorescence-encoded poly(methyl metharcylate) nanoparticles for a lateral flow assay detecting IgM autoantibodies in rheumatoid arthritis.

Rheumatoid arthritis (RA) belongs to the most often occurring autoimmune diseases in the world. For serological diagnosis, IgM auto-antibodies directed against the Fc portion of IgG referred to as rheumatoid factor are used as biomarkers. The autoantibody detection is usually done by ELISA. Such assays are reliable but are not suitable for point-of-care testing in contrast to lateral flow assays. Here, we report the development of a lateral flow assay based on carboxylated fluorescence-encoded poly(methyl methacrylate) nanoparticles. Poly(methyl methacrylate) is a non-toxic plastic with an excellent biocompatibility and high optical transparency which promises especially high sensitive fluorescence detection thereby leading to very sensitive assays. We could detect a positive signal in samples with a nephelometric reading down to 0.4 U/mL. By analyzing 30 sera of patients with a RA diagnosis and 34 sera of healthy test subjects we could confirm positive ELISA results in 72% of all cases and negative ELISA results in 97% of all cases.

Serological and viral genetic features of patients with COVID-19 in a selected German patient cohort-correlation with disease characteristics.

To study host-virus interactions after SARS coronavirus-2 (SARS-CoV-2) infection, genetic virus characteristics and the ensued humoral immune response were investigated for the first time. Fifty-five SARS-CoV-2-infected patients from the early pandemic phase were followed up including serological testing and whole genome sequencing. Anti-spike and nucleocapsid protein (S/N) IgG and IgM levels were determined by screening ELISA and IgG was further characterized by reactivity to S-subunit 1 (anti-S1), S-subunit 2 (anti-S2) and anti-N. In 55 patients, 90 genetic SARS-CoV-2 changes including 48 non-synonymous single nucleotide variants were identified. Phylogenetic analysis of the sequencing data showed a cluster representing a local outbreak and various family clusters. Anti-S/N and anti-N IgG were detected in 49 patients at an average of 83 days after blood collection. Anti-S/N IgM occurred significantly less frequently than IgG whereas anti-S2 was the least prevalent IgG reactivity (P < 0.05, respectively). Age and overweight were significantly associated with higher anti-S/N and anti-S1 IgG levels while age only with anti-N IgG (multiple regression, P < 0.05, respectively). Anti-S/N IgG/IgM levels, blood group A + , cardiovascular and tumour disease, NSP12 Q444H and ORF3a S177I were independent predictors of clinical characteristics with anti-S/N IgM being associated with the need for hospitalization (multivariate regression, P < 0.05, respectively). Anti-SARS-CoV-2 antibody generation was mainly affected by higher age and overweight in the present cohort. COVID-19 traits were associated with genetic SARS-CoV-2 variants, anti-S/N IgG/IgM levels, blood group A + and concomitant disease. Anti-S/N IgM was the only antibody associated with the need for hospitalization.

LEDGF/p75 Is Required for an Efficient DNA Damage Response.

Lens epithelium-derived growth factor splice variant of 75 kDa (LEDGF/p75) plays an important role in cancer, but its DNA-damage repair (DDR)-related implications are still not completely understood. Different LEDGF model cell lines were generated: a complete knock-out of LEDGF (KO) and re-expression of LEDGF/p75 or LEDGF/p52 using CRISPR/Cas9 technology. Their proliferation and migration capacity as well as their chemosensitivity were determined, which was followed by investigation of the DDR signaling pathways by Western blot and immunofluorescence. LEDGF-deficient cells exhibited a decreased proliferation and migration as well as an increased sensitivity toward etoposide. Moreover, LEDGF-depleted cells showed a significant reduction in the recruitment of downstream DDR-related proteins such as replication protein A 32 kDa subunit (RPA32) after exposure to etoposide. The re-expression of LEDGF/p75 rescued all knock-out effects. Surprisingly, untreated LEDGF KO cells showed an increased amount of DNA fragmentation combined with an increased formation of γH2AX and BRCA1. In contrast, the protein levels of ubiquitin-conjugating enzyme UBC13 and nuclear proteasome activator PA28γ were substantially reduced upon LEDGF KO. This study provides for the first time an insight that LEDGF is not only involved in the recruitment of CtIP but has also an effect on the ubiquitin-dependent regulation of DDR signaling molecules and highlights the role of LEDGF/p75 in homology-directed DNA repair.

countfitteR: efficient selection of count distributions to assess DNA damage.

BACKGROUND: DNA double-strand breaks can be counted as discrete foci by imaging techniques. In personalized medicine and pharmacology, the analysis of counting data is relevant for numerous applications, e.g., for cancer and aging research and the evaluation of drug efficacy. By default, it is assumed to follow the Poisson distribution. This assumption, however, may lead to biased results and faulty conclusions in datasets with excess zero values (zero-inflation), a variance larger than the mean (overdispersion), or both. In such cases, the assumption of a Poisson distribution would skew the estimation of mean and variance, and other models like the negative binomial (NB), zero-inflated Poisson or zero-inflated NB distributions should be employed. The model chosen has an influence on the parameter estimation (mean value and confidence interval). Yet the choice of the suitable distribution model is not trivial. METHODS: To support, simplify and objectify this process, we have developed the countfitteR software as an R package. We used a Bayesian approach for distribution model selection and the shiny web application framework for interactive data analysis. RESULTS: We show the application of our software based on examples of DNA double-strand break count data from phenotypic imaging by multiplex fluorescence microscopy. In analyzing numerous datasets of molecular pharmacological markers (phosphorylated histone H2AX and p53 binding protein), countfitteR demonstrated an equal or superior statistical performance compared to the usually employed two-step procedure, with an overall power of up to 98%. In addition, it still gave information in cases with no result at all from the two-step procedure. In our data sample we found that the NB distribution was the most frequent, with the Poisson distribution taking second place. CONCLUSIONS: countfitteR can perform an automated distribution model selection and thus support the data analysis and lead to objective statistically verifiable estimated values. Originally designed for the analysis of foci in biomedical image data, countfitteR can be used in a variety of areas where non-Poisson distributed counting data is prevalent.