Pathogen detection in RNA-seq data with Pathonoia.

BACKGROUND: Bacterial and viral infections may cause or exacerbate various human diseases and to detect microbes in tissue, one method of choice is RNA sequencing. The detection of specific microbes using RNA sequencing offers good sensitivity and specificity, but untargeted approaches suffer from high false positive rates and a lack of sensitivity for lowly abundant organisms. RESULTS: We introduce Pathonoia, an algorithm that detects viruses and bacteria in RNA sequencing data with high precision and recall. Pathonoia first applies an established k-mer based method for species identification and then aggregates this evidence over all reads in a sample. In addition, we provide an easy-to-use analysis framework that highlights potential microbe-host interactions by correlating the microbial to the host gene expression. Pathonoia outperforms state-of-the-art methods in microbial detection specificity, both on in silico and real datasets. CONCLUSION: Two case studies in human liver and brain show how Pathonoia can support novel hypotheses on microbial infection exacerbating disease. The Python package for Pathonoia sample analysis and a guided analysis Jupyter notebook for bulk RNAseq datasets are available on GitHub.

SEAweb: the small RNA Expression Atlas web application.

We present the Small RNA Expression Atlas (SEAweb), a web application that allows for the interactive querying, visualization and analysis of known and novel small RNAs across 10 organisms. It contains sRNA and pathogen expression information for over 4200 published samples with standardized search terms and ontologies. In addition, SEAweb allows for the interactive visualization and re-analysis of 879 differential expression and 514 classification comparisons. SEAweb's user model enables sRNA researchers to compare and re-analyze user-specific and published datasets, highlighting common and distinct sRNA expression patterns. We provide evidence for SEAweb's fidelity by (i) generating a set of 591 tissue specific miRNAs across 29 tissues, (ii) finding known and novel bacterial and viral infections across diseases and (iii) determining a Parkinson's disease-specific blood biomarker signature using novel data. We believe that SEAweb's simple semantic search interface, the flexible interactive reports and the user model with rich analysis capabilities will enable researchers to better understand the potential function and diagnostic value of sRNAs or pathogens across tissues, diseases and organisms.

Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn.

We investigate a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To cover large antigenic spaces, we develop Dolphyn, a method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn compresses the size of a peptide library by 78% compared to traditional tiling, increasing the antibody-reactive peptides from 10% to 31%. We find that the immune system develops antibodies to human gut bacteria-infecting viruses, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.

Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn.

We investigated a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To enhance this approach, we developed Dolphyn, a novel method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn improves the fraction of gut phage library peptides bound by antibodies from 10% to 31% in healthy individuals, while also reducing the number of synthesized peptides by 78%. In our study on gut phages, we discovered that the immune system develops antibodies to bacteria-infecting viruses in the human gut, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.

Histological activity despite normal ALT and IgG serum levels in patients with autoimmune hepatitis and cirrhosis.

BACKGROUND & AIMS: In autoimmune hepatitis (AIH), normal levels of transaminases and IgG define biochemical remission and are considered the best surrogate markers for histological remission. This study assessed whether this also applies to patients with AIH cirrhosis. METHODS: In this European multicentric study, we included 125 biopsies from 113 patients with AIH and histologically proven cirrhosis; 105 biopsies from 104 patients with AIH without cirrhosis served as controls. Biochemical parameters were available within 4 weeks of biopsy. AIH activity was graded according to the modified Hepatitis Activity Index (mHAI), with mHAI ≥4/18 considered to indicate risk of disease progression. RESULTS: In total, 47 out of 125 liver biopsies were obtained from patients with AIH cirrhosis and normal ALT levels at time of biopsy. Only 26% (12/47) of those livers showed histological remission (mHAI <4/18), whereas 36% (17/47) showed moderate to high histological activity (mHAI ≥6/18). In patients with noncirrhotic AIH, 88% (46/52 biopsies) of cases with normal ALT levels had histological remission and only 4% (2/52) had an mHAI ≥6/18 (p <0.001). The addition of IgG to define complete biochemical remission only slightly improved the association with histological remission in the limited number of patients with AIH cirrhosis available for analysis [29% (5/17) of biopsies with mHAI <4/18]. ALT correlated closely with mHAI in AIH without cirrhosis but poorly in AIH with cirrhosis. CONCLUSIONS: In contrast to patients with noncirrhotic AIH, in patients with AIH cirrhosis, who are at risk of disease progression, normal ALT levels and potentially also complete biochemical remission are poor surrogate markers of histological remission. Thus, new biomarkers are needed to monitor disease activity and progression in patients with AIH cirrhosis. LAY SUMMARY: Autoimmune hepatitis (AIH) is an inflammatory disease of the liver that usually responds to immunosuppressive therapy. Serum transaminases and IgG levels within the normal ranges define complete biochemical remission and are considered as surrogate markers for histological disease activity. Here, we show that those biochemical markers are not sufficient to indicate low disease activity in patients with AIH and already established cirrhosis. Consequently, until better biomarkers for disease activity are found, only liver biopsy can reliably indicate disease activity in the presence of cirrhosis. Additional investigations, such as measurements of liver stiffness, should be undertaken to monitor non-invasively for disease progression in patients with AIH and established cirrhosis.