Towards routine employment of computational tools for antimicrobial resistance determination via high-throughput sequencing.

Antimicrobial resistance (AMR) is a growing threat to public health and farming at large. In clinical and veterinary practice, timely characterization of the antibiotic susceptibility profile of bacterial infections is a crucial step in optimizing treatment. High-throughput sequencing is a promising option for clinical point-of-care and ecological surveillance, opening the opportunity to develop genotyping-based AMR determination as a possibly faster alternative to phenotypic testing. In the present work, we compare the performance of state-of-the-art methods for detection of AMR using high-throughput sequencing data from clinical settings. We consider five computational approaches based on alignment (AMRPlusPlus), deep learning (DeepARG), k-mer genomic signatures (KARGA, ResFinder) or hidden Markov models (Meta-MARC). We use an extensive collection of 585 isolates with available AMR resistance profiles determined by phenotypic tests across nine antibiotic classes. We show how the prediction landscape of AMR classifiers is highly heterogeneous, with balanced accuracy varying from 0.40 to 0.92. Although some algorithms-ResFinder, KARGA and AMRPlusPlus-exhibit overall better balanced accuracy than others, the high per-AMR-class variance and related findings suggest that: (1) all algorithms might be subject to sampling bias both in data repositories used for training and experimental/clinical settings; and (2) a portion of clinical samples might contain uncharacterized AMR genes that the algorithms-mostly trained on known AMR genes-fail to generalize upon. These results lead us to formulate practical advice for software configuration and application, and give suggestions for future study designs to further develop AMR prediction tools from proof-of-concept to bedside.

Establishment of international autoantibody reference standards for the detection of autoantibodies directed against PML bodies, GW bodies, and NuMA protein.

Objectives: Reference materials are important in the standardization of autoantibody testing and only a few are freely available for many known autoantibodies. Our goal was to develop three reference materials for antibodies to PML bodies/multiple nuclear dots (MND), antibodies to GW bodies (GWB), and antibodies to the nuclear mitotic apparatus (NuMA). Methods: Reference materials for identifying autoantibodies to MND (MND-REF), GWB (GWB-REF), and NuMA (NuMA-REF) were obtained from three donors and validated independently by seven laboratories. The sera were characterized using indirect immunofluorescence assay (IFA) on HEp-2 cell substrates including two-color immunofluorescence using antigen-specific markers, western blot (WB), immunoprecipitation (IP), line immunoassay (LIA), addressable laser bead immunoassay (ALBIA), enzyme-linked immunosorbent assay (ELISA), and immunoprecipitation-mass spectrometry (IP-MS). Results: MND-REF stained 6-20 discrete nuclear dots that colocalized with PML bodies. Antibodies to Sp100 and PML were detected by LIA and antibodies to Sp100 were also detected by ELISA. GWB-REF stained discrete cytoplasmic dots in interphase cells, which were confirmed to be GWB using two-color immunofluorescence. Anti-Ge-1 antibodies were identified in GWB-REF by ALBIA, IP, and IP-MS. All reference materials produced patterns at dilutions of 1:160 or greater. NuMA-REF produced fine speckled nuclear staining in interphase cells and staining of spindle fibers and spindle poles. The presence of antibodies to NuMA was verified by IP, WB, ALBIA, and IP-MS. Conclusions: MND-REF, GWB-REF, and NuMA-REF are suitable reference materials for the corresponding antinuclear antibodies staining patterns and will be accessible to qualified laboratories.

Establishment of an international autoantibody reference standard for human anti-DFS70 antibodies: proof-of-concept study for a novel Megapool strategy by pooling individual specific sera.

Background International autoantibody standards, traditionally based on material obtained from plasmapheresis of single subjects, represent individual immune response and may not comprehend the heterogeneity of the general population. The anti-DFS70 autoantibody yields a characteristic dense fine speckled (DFS) nuclear pattern on indirect immunofluorescence assay on HEp-2 cells (HEp-2 IFA) and speaks against autoimmunity. We propose a novel strategy for developing autoantibody reference standards, based on stepwise pooling of serum samples from hundreds of individuals with anti-DFS70 antibodies. Methods Within a 2-year period, serum samples were selected from routine HEp-2 IFA according to the following criteria: DFS HEp-2 IFA pattern at titer ≥1:640; anti-DFS70 reactivity in three analyte-specific tests (Western blot [WB], enzyme-linked immunosorbent assay [ELISA] and chemiluminescent immunoassay [CLIA]). Aliquots of individual samples were combined into progressively larger pools with stepwise validation of intermediary pools as for individual samples. Validated intermediary pools were merged into a final pool for lyophilization. Results A total of 741 validated samples yielded a 750 mL final pool that was lyophilized into thousands of 200 µL-aliquots. Reconstituted aliquots yielded the expected anti-DFS70 reactivity in ELISA, CLIA and WB, as well as high-titer DFS HEp-2 IFA pattern. The appropriate anti-DFS70 reactivity of the lyophilized pool was confirmed by seven international expert centers, using HEp-2 IFA, ELISA, WB and immunoprecipitation. Conclusions This proof-of-concept study provides an innovative and efficient strategy to build serum reference standards for autoantibody testing. The anti-DFS70 standard will integrate the panel of standards of Autoantibody Standardization Committee (ASC, www.autoab.org), contributing to education for proper assay validation and interpretation of the DFS pattern and other HEp-2 IFA patterns.

Anti-DFS70 Antibodies Among Patient and Healthy Population Cohorts in China: Results From a Multicenter Training Program Showing Spontaneous Abortion and Pediatric Systemic Autoimmune Rheumatic Diseases Are Common in Anti-DFS70 Positive Patients.

Objective: Anti-DFS70 antibodies correlating with the nuclear dense fine speckled (DFS) pattern in the HEp-2 indirect immunofluorescence assay (IFA) are less common in patients with systemic autoimmune rheumatic disease (SARD) than in healthy subjects and their clinical associations remain elusive. We hosted a multi-center HEp-2 IFA training program to improve the ability of clinical laboratories to recognize the DFS pattern and to investigate the prevalence and relevance of anti-DFS70 antibodies. Methods: DFS pattern sera identified by HEp-2 IFA in 29 centers in China were redirected to a central laboratory for anti-DFS70 testing by line immunoblot assay (LIA), enzyme-linked immunosorbent assay (ELISA), and IFA with HEp-2 ELITE/DFS70-KO substrate. Anti-extractable nuclear antigen antibodies were measured by LIA and the clinical relevance was examined in adult and pediatric patients. Results: HEp-2 IFA positive rate and DFS pattern in positive sera were 36.2% (34,417/95,131) and 1.7% (582/34,417) in the patient cohort, and 10.0% (423/4,234) and 7.8% (33/423) in a healthy population, respectively. Anti-DFS70 prevalence among sera presenting the DFS pattern was 96.0, 93.7, and 49.6% by ELISA, LIA, and HEp-2 ELITE, respectively. 15.5% (52/336) of adult and 50.0% (20/40) of pediatric anti-DFS70 positive patients were diagnosed with SARD. Diseases most common in anti-DFS70 positive patients were spontaneous abortion (28.0%) in adults and juvenile idiopathic arthritis (22.5%) in pediatric patients. Conclusion: Accurate DFS pattern identification increased the detection rate of anti-DFS70 antibodies by ELISA and LIA. Anti-DFS70 antibodies are remarkably high in cases of spontaneous abortion and in pediatric SARD patients, but not prevalent in adult SARD patients.

Emerging microRNAs in cancer diagnosis, progression, and immune surveillance.

MicroRNAs (miRNAs) are small noncoding RNAs that function in post-transcriptional regulation of gene expression. Dysregulation of miRNAs has been reported in different stages of cancer development and progression. This dysregulation results in different miRNA profiles between cancer and normal tissues. Many studies have shown a significant correlation between miRNA profile and cancer diagnosis and prognosis. Additionally, since a single miRNA regulates multiple mRNA targets, miRNAs dysregulation can affect several pathways involved in cancer development. Finally, due to their regulatory role in immune cell development, many recent studies have reported that certain miRNAs play key roles in cancer immunology. In this brief review, we discuss the role of miR-21 and miR-375 in the RAS pathway as well as their role in cancer diagnosis and progression, along with the role of other select miRNAs in cancer immune surveillance.