Background: In the past urine was considered sterile. Through the introduction of next generation sequencing, it has become clear that a urinary microbiome exists. Acute kidney injury (AKI) represents a major threat to kidney transplant recipients. Remarkable changes in the urinary metabolome occur during AKI, which may influence the urinary microbiome. To our knowledge, this is the first study that examines the urinary microbiome in renal transplant recipients (RTX) and non-transplant recipients (nRTX) at time of AKI.Methods: In this cross-sectional pilot-study the urinary microbiome of 21 RTX and 9 nRTX with AKI was examined. Clean catch morning urine samples were obtained from all patients on the first day of AKI diagnosis. AKI was defined according to KDIGO guidelines. Urinary microbiota and the urinary metabolome during AKI were assessed in one patient. 16S rRNA sequencing was performed. Sequences were processed using UPARSE-pipeline for operational taxonomic units (OTU) and taxon finding.Results: We successfully extracted and sequenced bacterial DNA from 100% of the urine samples. All 30 patients revealed at least 106,138 reads. 319 OTU and 211 different genera were identified. The microbiotic diversity richness in the RTX group was no different from the nRTX group. Eighteen genera were solely present in nRTX and 7 in RTX.Conclusions: The urinary microbiome at time of AKI showed different bacterial genera in RTX compared to nRTX. The nRTX group exhibited no different diversity to the RTX group. Irrespective of the status of a previous renal transplantation, the urinary microbiome comprised > 210 different genera. An intraindividual change in microbiota diversity and richness was observed in one study patient during recovery from AKI.

Patients with multiple myeloma (MM) are a heterogenous, immunocompromised group with increased risk for COVID-19 morbidity and mortality but impaired responses to primary mRNA SARS-CoV-2 vaccination. The effects of booster vaccinations and breakthrough infections (BTIs) on antibody (Ab) levels and cross-protection to variants of concern (VOCs) are, however, not sufficiently evaluated. Therefore, we analysed humoral and cellular vaccine responses in MM patients stratified according to disease stage/treatment into group (1) monoclonal gammopathy of undetermined significance, (2) after stem cell transplant (SCT) without immunotherapy (IT), (3) after SCT with IT, and (4) progressed MM, and in healthy subjects (prospective cohort study). In contrast to SARS-CoV-2 hu-1-specific Ab levels, Omicron-specific Abs and their cross-neutralisation capacity remained low even after three booster doses in a majority of MM patients. In particular, progressed MM patients receiving anti-CD38 mAb and those after SCT with IT were Ab low responders and showed delayed formation of spike-specific B memory cells. However, MM patients with hybrid immunity (i.e., vaccination and breakthrough infection) had improved cross-neutralisation capacity against VOCs, yet in the absence of severe COVID-19 disease. Our results indicate that MM patients require frequent variant-adapted booster vaccinations and/or changes to other vaccine formulations/platforms, which might have similar immunological effects as BTIs.

The target of rapamycin complex 1 (TORC1) is a highly conserved multiprotein complex that functions in many cellular processes, including cell growth and cell cycle progression. In this study, we define a novel role for TORC1 as a critical regulator of nuclear microtubule (MT) dynamics in the budding yeast Saccharomyces cerevisiae. This activity requires interactions between EB1 and CLIP-170 plus end–tracking protein (+TIP) family members with the TORC1 subunit Kog1/Raptor, which in turn allow the TORC1 proximal kinase Sch9/S6K1 to regulate the MT polymerase Stu2/XMAP215. Sch9-dependent phosphorylation of Stu2 adjacent to a nuclear export signal prevents nuclear accumulation of Stu2 before cells enter mitosis. Mutants impaired in +TIP–TORC1 interactions or Stu2 nuclear export show increased nuclear but not cytoplasmic MT length and display nuclear fusion, spindle positioning, and elongation kinetics defects. Our results reveal key mechanisms by which TORC1 signaling controls Stu2 localization and thereby contributes to proper MT cytoskeletal organization in interphase and mitosis.

The analysis of ultra-low input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here we report a comprehensive workflow that includes optimized strategies for all steps from cell lysis to data analysis. Thanks to convenient to handle 1 μL sample volume and standardized 384 well plates the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using the CellenONE®, which allows for highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced μ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA) and data-independent acquisition (DIA), and commonly used advanced data-analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single cell level input in a 20-min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination.