No abstract

Fungal infections are a rising threat to our immunocompromised patient population as well as other non-immunocompromised patients with various medical conditions. However, little progress has been made in the past decade to improve fungal diagnostics. To jointly address this diagnostic challenge, the Fungal Diagnostics Laboratory Consortium (FDLC) was recently created. The FDLC consists of 26 laboratories from the United States and Canada that routinely provide fungal diagnostic services for patient care. A survey of fungal diagnostic capacity among the 26 members of the FDLC was recently completed, identifying the following diagnostic gaps: lack of molecular detection of mucormycosis; lack of an optimal diagnostic algorithm incorporating fungal biomarkers and molecular tools for early and accurate diagnosis of Pneumocystis pneumonia, aspergillosis, candidemia, and endemic mycoses; lack of a standardized molecular approach to identify fungal pathogens directly in formalin-fixed paraffin-embedded tissues; lack of robust databases to enhance mold identification with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; suboptimal diagnostic approaches for mold blood cultures, tissue culture processing for Mucorales, and fungal respiratory cultures for cystic fibrosis patients; inadequate capacity for fungal point-of-care testing, to detect and identify new, emerging or under-recognized, rare or uncommon fungal pathogens, and performance of antifungal susceptibility testing. In this commentary, the FDLC delineates the most pressing unmet diagnostic needs and provides expert opinion on how to fulfill them. Most importantly, the FDLC provides a robust laboratory network to tackle these diagnostic gaps and ultimately to improve and enhance the clinical laboratory’s capability to rapidly and accurately diagnose fungal infections.

Invasive fungal infections are increasing in prevalence because of an expanding population of immunocompromised individuals. To reduce morbidity and mortality, it is critical to accurately identify fungal pathogens to guide treatment. Current methods rely on histopathology, fungal culture, and serology, which are often insufficient for diagnosis. Herein, we describe the use of a laboratorydeveloped internal transcribed spaceretargeted amplicon-based next-generation sequencing (NGS) assay for the identification of fungal etiology in fungal stainepositive formalin-fixed, paraffinembedded tissues by using Illumina MiSeq. A total of 44 specimens from 35 patients were included in this study, with varying degrees of fungal burden from multiple anatomic sites. NGS identified 20 unique species across the 54 total organisms detected, including 40 molds, 10 yeasts, and 4 dimorphic fungi. The histopathologic morphology and the organisms suspected by surgical pathologist were compared with the organisms identified by NGS, with 100% (44/44) and 93.2% (41/44) concordance, respectively. In contrast, fungal culture only provided an identification in 27.3% (12/44) of specimens. We demonstrated that NGS is a powerful method for accurate and unbiased fungal identification in formalin-fixed, paraffin-embedded tissues. A retrospective evaluation of the clinical utility of the NGS results also suggests this technology can potentially improve both the speed and the accuracy of diagnosis for invasive fungal infections.

Calcitriol, the active form of vitamin D, has been well documented to act directly on immune cells and malignant cells. Activated T cells are one of the best characterized targets of calcitriol, with effects including decreasing inflammatory cytokine output and promoting anti-inflammatory cytokine production. However, the effects of calcitriol on natural killer (NK) cells are less clear. Reports suggest that only immature NK cell populations are affected by calcitriol treatment resulting in impaired cytotoxic function and cytokine production, while mature NK cells may have little or no response. NK cell large granular lymphocyte leukemia (NK-LGLL) is a rare leukemia with CD3-CD16+CD56+ NK cell clonal expansion. The current standard treatments are immunosuppressant therapies, which are not curative. The Janus kinase (JAK) – signal transducer and activator of transcription (STAT) pathway is hyperactivated in LGLL and is one pathway of interest in new drug target investigations. We previously demonstrated the ability of calcitriol to decrease STAT1 tyrosine 701 (p-STAT1) and STAT3 tyrosine 705 (p-STAT3) phosphorylation as well as inflammatory cytokine output of T cell large granular lymphocyte leukemia cells, but did not determine the effects of calcitriol on NK-LGLL. Therefore, in the present study, we investigated whether NKL cells, a model of NK-LGLL, and NK-LGLL patient peripheral blood mononuclear cells (PBMCs) are susceptible to treatment with calcitriol or seocalcitol (EB1089), a potent analog of calcitriol. NKL cells are dependent on interleukin (IL)-2 for survival and we show here for the first time that treatment with IL-2 induced tyrosine phosphorylation of STATs 1 through 6. Both calcitriol and EB1089 caused significant upregulation of the vitamin D receptor (VDR). IL-2 induction of p-STAT1 and p-STAT3 phosphorylation was significantly decreased after calcitriol or EB1089 treatment. Additionally, IL-10, interferon (IFN)-γ, and FMS-like tyrosine kinase 3 ligand (Flt-3L) extracellular output was significantly decreased at 100 nM EB1089 and intracellular IL-10 was decreased with either calcitriol or EB1089 treatment. We treated NK-LGLL patient PBMCs with calcitriol or EB1089 and found decreased p-STAT1 and p-STAT3 while VDR increased, which matched the NKL cell line data. We then measured 75 serum cytokines in NK-LGLL patients (n=8) vs. age- and sex-matched normal healthy donors (n=8), which is the first serum cytokine study for this LGLL subtype. We identified 15 cytokines, including IL-10 and Flt-3L, which were significantly different between normal donors and NK-LGLL patients. Overall, our results suggest that activating the vitamin D pathway could be a mechanism to decrease STAT1 and 3 activation and inflammatory cytokine output in NKLGLL patients.

Large granular lymphocyte (LGL) leukemia is a rare hematological disorder with expansion of the T‐cell or natural killer (NK) cell lineage. Signal transducer and activator of transcription 3 (STAT3) exhibits somatic activating mutations in 30%‐40% of LGL leukemia cases. Transcriptional targets of STAT3 include inflammatory cytokines, thus previous studies have measured cytokine levels of LGL leukemia patients compared to normal donors. Sphingolipid metabolism is a growing area of cancer research, with efforts focused on drug discovery. To date, no studies have examined serum sphingolipids in LGL leukemia patients, and only one study compared a subset of cytokines between the T‐LGL and NK‐LGL subtypes. Therefore, here, we included both LGL leukemia subtypes with the goals of (a) measuring serum sphingolipids for the first time, (b) measuring cytokines to find distinctions between the subtypes, and (c) establishing relationships with STAT3 mutations and clinical data. The serum analyses identified cytokines (EGF, IP‐10, G‐CSF) and sphingolipids (SMC22, SMC24, SMC20, LysoSM) significantly different in the LGL leukemia group compared to normal donors. In a mixed STAT3 mutation group, D661Y samples exhibited the highest mean corpuscular volume (MCV) values. We explored this further by expanding the cohort to include larger groups of single STAT3 mutations. Male D661Y STAT3 samples had lower Hgb and higher MCV compared to wild type (WT) or Y640F counterparts. This is the first report examining large groups of individual STAT3 mutations. Overall, our results revealed novel serum biomarkers and evidence that D661Y mutation may show different clinical manifestation compared to WT or Y640F STAT3.

Chronic pulmonary aspergillosis (CPA) refers to a spectrum of Aspergillus-mediated disease that is associated with high morbidity and mortality, with its true prevalence vastly underestimated. The diagnosis of CPA includes characteristic radiographical findings in conjunction with persistent and systemic symptoms present for at least three months, and evidence of Aspergillus infection. Traditionally, Aspergillus infection has been confirmed through histopathology and microbiological studies, including fungal culture and serology, but these methodologies have limitations that are discussed in this review. The treatment of CPA requires an individualized approach and consideration of both medical and surgical options. Most Aspergillus species are considered susceptible to mold-active triazoles, echinocandins, and amphotericin B; however, antifungal resistance is emerging and well documented, demonstrating the need for novel therapies and antifungal susceptibility testing that correlates with clinical response. Here, we describe the clinical presentation, diagnosis, and treatment of CPA, with an emphasis on the strengths and pitfalls of diagnostic and treatment approaches, as well as future directions, including whole genome sequencing and metagenomic sequencing. The advancement of molecular technology enables rapid and precise species level identification, and the determination of molecular mechanisms of resistance, bridging the clinical infectious disease, anatomical pathology, microbiology, and molecular biology disciplines.

Acinetobacter baumannii is associated with both hospital-acquired infections and community-acquired pneumonia (CAP). Here, we describe a novel strain of A. baumannii in a case of CAP in a previously healthy rural villager from Central Eastern China. Materials and Methods: A. baumannii isolated from the patient (LS01) was compared to well-characterized pathogenic strain (AB5075), nosocomial circulating strain in China (ZJ06), and wild-type strain (ATCC17978). Growth rate studies were conducted under different environmental stressors, and virulence studies were performed using Galleria mellonella larvae. Whole genome sequencing (WGS) was performed using MinIon and MiSeq. Center for Genomic Epidemiology, CLCbio, Geneious, and Virulence Factors of Pathogenic Bacteria database were used for genomic analysis. Results: LS01 grew significantly faster at 37°C and 42°C and in the presence of zinc compared to other strains. LS01 was more virulent in G. mellonella, killing all larvae within 8 h. Although WGS revealed 44 virulence genes, these genes were also present in the other strains. While two chromosomally encoded β-lactamases were identified, there were no plasmids identified and LS01 was pan-susceptible to all antibiotics tested. Phylogenetic analysis revealed that the closest related strains were only 72.552% identical, supporting a novel strain. Conclusion: LS01 is a novel strain of hypervirulent yet pan-drug susceptible A. baumannii isolated from a patient with no prior hospitalizations, sick contacts, or any of the typical risk factors. This raises concerns for an emerging pathogen, and more epidemiological studies should be conducted to assess the prevalence of this A. baumannii strain.

Antimicrobial susceptibility testing (AST) is a standard clinical procedure used to quantify antimicrobial resistance (AMR). Currently, the gold standard method requires incubation for 18-24 h and subsequent inspection for growth by a trained medical technologist. We demonstrate an automated, cost-effective optical system that delivers early AST results, minimizing incubation time and eliminating human errors, while remaining compatible with standard phenotypic assay workflow. The system is composed of cost-effective components and eliminates the need for optomechanical scanning. A neural network processes the captured optical intensity information from an array of fiber optic cables to determine whether bacterial growth has occurred in each well of a 96-well microplate. When the system was blindly tested on isolates from 33 patients with Staphylococcus aureus infections, 95.03% of all the wells containing growth were correctly identified using our neural network, with an average of 5.72 h of incubation time required to identify growth. 90% of all wells (growth and nogrowth) were correctly classified after 7 h, and 95% after 10.5 h. Our deep learning-based optical system met the FDA-defined criteria for essential and categorical agreements for all 14 antibiotics tested after an average of 6.13 h and 6.98 h, respectively. Furthermore, our system met the FDA criteria for major and very major error rates for 11 of 12 possible drugs after an average of 4.02 h, and 9 of 13 possible drugs after an average of 9.39 h, respectively. This system could enable faster, inexpensive, automated AST, especially in resource-limited settings, helping to mitigate the rise of global AMR. time for wells with and without turbidity are shown in Figures 1g-i.