Universal digital high-resolution melting for the detection of pulmonary mold infections.

Invasive mold infections (IMIs) are associated with high morbidity, particularly in immunocompromised patients, with mortality rates between 40% and 80%. Early initiation of appropriate antifungal therapy can substantially improve outcomes, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high-resolution melting (U-dHRM) analysis may enable rapid and robust diagnoses of IMI. A universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these pathogen curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons. U-dHRM achieved 97% overall fungal organism identification accuracy and a turnaround time of ~4 hrs. U-dHRM detected pathogenic molds (Aspergillus, Mucorales, Lomentospora, and Fusarium) in 73% of 30 samples classified as IMI, including mixed infections. Specificity was optimized by requiring the number of pathogenic mold curves detected in a sample to be >8 and a sample volume to be 1 mL, which resulted in 100% specificity in 21 at-risk patients without IMI. U-dHRM showed promise as a separate or combination diagnostic approach to standard mycological tests. U-dHRM's speed, ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples, and detect emerging opportunistic pathogens may aid treatment decisions, improving patient outcomes. IMPORTANCE: Improvements in diagnostics for invasive mold infections are urgently needed. This work presents a new molecular detection approach that addresses technical and workflow challenges to provide fast pathogen detection, identification, and quantification that could inform treatment to improve patient outcomes.

Prioritization of ethical concerns regarding HIV molecular epidemiology by public health practitioners and researchers.

BACKGROUND: HIV molecular epidemiology (HIV ME) can support the early detection of emerging clusters of new HIV infections by combining HIV sequence data routinely obtained during the clinical treatment of people living with HIV with behavioral, geographic, and sociodemographic information. While information about emerging clusters promises to facilitate HIV prevention and treatment efforts, the use of this data also raises several ethical concerns. We sought to assess how those working on the frontlines of HIV ME, specifically public health practitioners (PHPs) and researchers, prioritized these issues. METHODS: Ethical issues were identified through literature review, qualitative in-depth interviews, and stakeholder engagement. PHPs and researchers using HIV ME prioritized the issues using best-worst scaling (BWS). A balanced incomplete block design was used to generate 11 choice tasks each consisting of a sub-set of 5 ethical concerns. In each task, respondents were asked to assess the most and least concerning issue. Data were analyzed using conditional logit, with a Swait-Louviere test of poolability. Latent class analysis was then used to explore preference heterogeneity. RESULTS: In total, 57 respondents completed the BWS experiment May-June 2023 with the Swait-Louviere test indicating that researchers and PHPs could be pooled (p = 0.512). Latent class analysis identified two classes, those highlighting "Harms" (n = 29) (prioritizing concerns about potential risk of legal prosecution, individual harm, and group stigma) and those highlighting "Utility" (n = 28) (prioritizing concerns about limited evidence, resource allocation, non-disclosure of data use for HIV ME, and the potential to infer the directionality of HIV transmission). There were no differences in the characteristics of members across classes. CONCLUSIONS: The ethical issues of HIV ME vary in importance among stakeholders, reflecting different perspectives on the potential impact and usefulness of the data. Knowing these differences exist can directly inform the focus of future deliberations about the policies and practices of HIV ME in the United States.

Mitochondrial DNA and Electron Transport Chain Protein Levels Are Altered in Peripheral Nerve Tissues from Donors with HIV Sensory Neuropathy: A Pilot Study.

Distal sensory polyneuropathy (DSP) and distal neuropathic pain (DNP) remain significant challenges for older people with HIV (PWH), necessitating enhanced clinical attention. HIV and certain antiretroviral therapies (ARTs) can compromise mitochondrial function and impact mitochondrial DNA (mtDNA) replication, which is linked to DSP in ART-treated PWH. This study investigated mtDNA, mitochondrial fission and fusion proteins, and mitochondrial electron transport chain protein changes in the dorsal root ganglions (DRGs) and sural nerves (SuNs) of 11 autopsied PWH. In antemortem standardized assessments, six had no or one sign of DSP, while five exhibited two or more DSP signs. Digital droplet polymerase chain reaction was used to measure mtDNA quantity and the common deletions in isolated DNA. We found lower mtDNA copy numbers in DSP+ donors. SuNs exhibited a higher proportion of mtDNA common deletion than DRGs in both groups. Mitochondrial electron transport chain (ETC) proteins were altered in the DRGs of DSP+ compared to DSP- donors, particularly Complex I. These findings suggest that reduced mtDNA quantity and increased common deletion abundance may contribute to DSP in PWH, indicating diminished mitochondrial activity in the sensory neurons. Accumulated ETC proteins in the DRG imply impaired mitochondrial transport to the sensory neuron's distal portion. Identifying molecules to safeguard mitochondrial integrity could aid in treating or preventing HIV-associated peripheral neuropathy.

Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology.

BACKGROUND: HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data. METHODS: We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively. RESULTS: Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network. CONCLUSION: Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed.

Recent HIV Infection among men who have sex with men and transgender women in Tijuana

ABSTRACT OBJECTIVE To characterize recent HIV infections among newly diagnosed men who have sex with men and transgender women in Tijuana. METHODS Limiting Antigen (LAg)-Avidity testing was performed to detect recent HIV infection within a cohort of newly-diagnosed men who have sex with men and transgender women in Tijuana. Logistic regression was used to determine characteristics associated with recent infection. A partial transmission network was inferred using HIV-1 pol sequences. Tamura-Nei 93 genetic distances were measured between all pairs of sequences, and the network was constructed by inferring putative transmission links (genetic distances ≤ 1.5%). We assessed whether recent infection was associated with clustering within the inferred network. RESULTS Recent infection was detected in 11% (22/194) of newly-diagnosed participants. Out of the participants with sequence data, 60% (9/15) with recent infection clustered compared with 31% (43/139) with chronic infection. Two recent infections belonged to the same cluster. In adjusted analyses, recent infection was associated with years of residence in Tijuana (OR = 1.5; 95%CI 1.01-1.09), cocaine use (past month) (OR = 8.50; 95%CI 1.99-28.17), and ever experiencing sexual abuse (OR = 2.85; 95%CI 1.03-7.85). DISCUSSION A total of 11% of men newly diagnosed with HIV who have sex with men and transgender women in Tijuana were recently infected. The general lack of clustering between participants with recent infection suggests continued onward HIV transmission rather than an outbreak within a particular cluster.