Objectives: Infections of the ascitic fluid are serious conditions that require rapid diagnosis and treatment. Ascites is often accompanied by other critical pathologies such as gastrointestinal bleeding and bowel perforation, and infection increases the risk of mortality in intensive care patients. Owing to a relatively low success rate of conventional culture methods in identifying the responsible pathogens, new methods may be helpful to guide antimicrobial therapy and to refine empirical regimens. Here, we aim to assess outcomes and to identify responsible pathogens in ascitic fluid infections, in order to improve patients’ care and to guide empirical therapy. Methods: Between October 2019 and March 2021, we prospectively collected 50 ascitic fluid samples from ICU patients with suspected infection. Beside standard culture-based microbiology methods, excess fluid underwent DNA isolation and was analyzed by next- and third-generation sequencing (NGS) methods. Results: NGS-based methods had higher sensitivity in detecting additional pathogenic bacteria such as E. faecalis and Klebsiella in 33 out of 50 (66%) ascitic fluid samples compared with culture-based methods (26%). Anaerobic bacteria were especially identified by sequencing-based methods in 28 samples (56%), in comparison with only three samples in culture. Analysis of clinical data showed a correlation between sequencing results and various clinical parameters such as peritonitis and hospitalization outcomes. Conclusions: Our results show that, in ascitic fluid infections, NGS-based methods have a higher sensitivity for the identification of clinically relevant pathogens than standard microbiological culture diagnostics, especially in detecting hard-to-culture anaerobic bacteria. Patients with such infections may benefit from the use of NGS methods by the possibility of earlier and better targeted antimicrobial therapy, which has the potential to lower the high morbidity and mortality in critically ill patients with ascitic bacterial infection.

Introduction: Alterations of the gut microbiome are involved in the pathogenesis of Crohn’s disease (CD). The role of fungi in this context is unclear. This study aimed to determine postoperative changes in the bacterial and fungal gut communities of CD patients undergoing intestinal resection, and to evaluate interactions between the bacteriome and mycobiome and their impact on the patients’ outcome.Methods: We report a subgroup analysis of a prospective cohort study, focusing on 10 CD patients whose fecal samples were collected for bacterial 16S rRNA and fungal ITS2 genes next-generation sequencing the day before surgery and on the 5th or 6th postoperative day.Results: No significant differences in bacterial and fungal diversity were observed between preoperative and postoperative stool samples. By in-depth analysis, significant postoperative abundance changes of bacteria and fungi and 17 interkingdom correlations were detected. Network analysis identified 13 microbial clusters in the perioperative gut communities, revealing symbiotic and competitive interactions. Relevant factors were gender, age, BMI, lifestyle habits (smoking, alcohol consumption) and surgical technique. Postoperative abundance changes and identified clusters were associated with clinical outcomes (length of hospital stay, complications) and levels of inflammatory markers.Conclusions: Our findings highlight the importance of dissecting the interactions of gut bacterial and fungal communities in CD patients and their potential influence on postoperative and disease outcomes.

The highly conserved CHCHD2 and CHCHD10 are small mitochondrial proteins residing in the intermembrane space. Recently, mutations in the genes encoding these proteins have been linked to severe disorders, including Parkinson’s disease and amyotrophic lateral sclerosis. In cultured cells, a small fraction of CHCHD2 and CHCHD10 oligomerize to form a high molecular weight complex of unknown function. Here, we generated a whole-body Chchd2 knockout mouse to investigate the in vivo role of CHCHD2 and its protein complex. We show that CHCHD2 is crucial for sustaining full motor capacity, normal striatal dopamine levels, and lipid homeostasis in the brain of adult male mice. We also demonstrate that in mouse tissues, CHCHD2 and CHCHD10 exist exclusively as a high molecular weight complex, whose levels are finely tuned under physiological conditions. In response to mitochondrial dysfunction, the abundance and size of the CHCHD2-CHCHD10 complex increase, a mechanism conserved across different tissues. Although the loss of CHCHD2 does not abolish CHCHD10 oligomerization, it enhances cell vulnerability to mitochondrial stress, suggesting that CHCHD2 is protective against mitochondrial damage. Our findings uncover the role of CHCHD2 in preserving tissue homeostasis and provide important insights into the involvement of the CHCHD2-CHCHD10 complex in human diseases.

Objectives: Ascites, often associated with critical pathologies such as liver cirrhosis or bowel perforation, can be complicated by fungal infection, increasing mortality especially in intensive care settings and demanding rapid diagnosis and adequate treatment. Traditional microbiological diagnostic methods have limited sensitivity in accurately identifying fungal pathogens in ascitic fluid. Alternative diagnostic methods may offer important insights to enable guiding of antifungal therapy and refining empirical treatment strategies. The objective of this study was to evaluate the potential of next-generation sequencing methods to identify specific fungal pathogens responsible for ascitic fluid infections.Methods: We prospectively collected 50 ascitic fluid samples from ICU patients with suspected ascites infection. In addition to standard culture-based microbiological testing, an ascitic fluid aliquot underwent fungal DNA isolation and was analyzed by next-generation sequencing (NGS) methods for identification of fungal species.Results: Of 50 ascitic samples collected, five samples showed growth of Candida spp. in culture. After DNA isolation and ITS2 PCR, detectable amplification was achieved in 10 samples. Sequencing of the 50 patients’ samples identified facultative pathogenic fungi in 19 patients. In 15 cases, culture alone would not have permitted the identification of all facultative pathogenic fungi. The identification of fungal DNA by sequencing was significantly associated with poor patient outcome and a number of clinical parameters.Conclusions: Our results show a higher sensitivity for NGS-based diagnostic methods in the identification of ascitic fluid fungal infections compared to culture-based diagnostics. This may be beneficial especially for patients in a critical care setting, who have an increased prevalence of comorbidities and high mortality. The implementation of such methods in standard diagnosis will require increased standardization of the workflows and interpretation of the sequencing results with respect to patients’ clinical picture.

Proteomics by mass spectrometry has rapidly matured from a niche method into a standard tool. The recent 10‐year trajectory of single‐cell proteomics has opened a new biological dimension for studying disease. Mitochondrial diseases, with their pronounced cell‐to‐cell heterogeneity, are particularly, well‐suited to these methods. Here, we discuss how this approach can serve as an orthogonal functional layer for rare disease diagnostics. We trace the evolution of rare disease diagnostics from biochemical enzyme assays through genomics, transcriptomics, proteomics and metabolomics, highlighting incremental gains in diagnostic yield from individual omics layers and their integration. We discuss the limitations of bulk approaches in capturing the functional consequences of genetic perturbations, the new opportunities opened up by single‐cell measurements and how spatial single‐cell proteomics can further enrich the biological signal of affected cells in diagnostic tissues. We observe that the persisting diagnostic gap reflects not only technological limitations but, increasingly, challenges in data sharing and infrastructure as well as interpretive frameworks for functional molecular evidence. In this context, we consider opportunities for artificial intelligence and the ethical dimensions of single‐cell proteomics in rare disease diagnostics. Finally, we propose a single‐cell deep visual proteomics (scDVP) framework for clinical diagnostics of rare diseases with cell‐to‐cell variability, arguing that mitochondrial diseases are an ideal proof‐of‐concept.