Mycobacterial Mutagenesis and Drug Resistance Are Controlled by Phosphorylation- and Cardiolipin-Mediated Inhibition of the RecA Coprotease.

Infection with Mycobacterium tuberculosis continues to cause substantial human mortality, in part because of the emergence of antimicrobial resistance. Antimicrobial resistance in tuberculosis is solely the result of chromosomal mutations that modify drug activators or targets, yet the mechanisms controlling the mycobacterial DNA-damage response (DDR) remain incompletely defined. Here, we identify RecA serine 207 as a multifunctional signaling hub that controls the DDR in mycobacteria. RecA S207 is phosphorylated after DNA damage, which suppresses the emergence of antibiotic resistance by selectively inhibiting the LexA coprotease function of RecA without affecting its ATPase or strand exchange functions. Additionally, RecA associates with the cytoplasmic membrane during the mycobacterial DDR, where cardiolipin can specifically inhibit the LexA coprotease function of unmodified, but not S207 phosphorylated, RecA. These findings reveal that RecA S207 controls mutagenesis and antibiotic resistance in mycobacteria through phosphorylation and cardiolipin-mediated inhibition of RecA coprotease function.

Behavioral Functioning and Quality of Life in South African Children Living with HIV on Antiretroviral Therapy.

This study examined behavioral functioning and quality of life in South African children living with perinatally acquired HIV. Compared with controls, children living with perinatally acquired HIV had a higher mean total difficulties score assessed by the Strengths and Difficulties Questionnaire and lower mean quality of life scores assessed by the Pediatric Quality of Life Inventory.

Role of pre-stroke immunity in ischemic stroke mechanism among patients with HIV.

Individuals with HIV are at a higher risk of stroke compared to uninfected populations. The role of HIV-related immunosuppression in stroke mechanism is uncertain. Our aim is to test the hypothesis that stroke mechanisms among HIV+ individuals vary according to preceding CD4 counts. We carried out a retrospective chart review of inpatient admissions for ICD-9 defined ischemic events (TIA or stroke) in HIV+ individuals from 2002 to 2016 at a tertiary care center. Stroke mechanisms were ascertained based on radiographic and clinical presentation, and adjudicated by the treating team and confirmed separately by a vascular neurologist. Vascular risk factors, use of antiretroviral drugs (ARVs), nadir CD4 and current CD4 counts (cells/mm3) were captured to build logistic regressions and generalized linear models to calculate the odds ratios (OR) and beta estimates with their respective 95% confidence intervals. We found that among 115 cases (median age 52, 64% men), stroke mechanisms were 22% due to large artery atherosclerosis (LAA), 17% small artery disease, 16% infectious, 8% cardioembolic, 21% cryptogenic, and 16% other etiologies. The median nadir CD4-count was 153 (IQR 22-274), and 312 (IQR 88-518) at the time of stroke, and 53% were on ARVs. LAA was more common with longer HIV infection (OR 1.1 per year, 1.0-1.2) and nadir CD4 counts <200 (OR 6.7, 1.4-31.9). Stroke due to LAA was associated with higher CD4 count the year prior to stroke (B = 0.009, P = 0.06 for the interaction) independent of CD4 nadir <200 (B = 1.88, P = 0.035). We concluded that in this sample, LAA was the most frequent stroke mechanism among HIV+ individuals with nadir CD4 < 200 but higher CD4 counts near the time of stroke. Determining the association between pre-stroke immune status and stroke mechanisms may allow a targeted approach to stroke prevention.

Site-2 protease substrate specificity and coupling in trans by a PDZ-substrate adapter protein.

Site-2 proteases (S2Ps) are intramembrane metalloproteases that cleave transmembrane substrates in all domains of life. Many S2Ps, including human S2P and Mycobacterium tuberculosis Rip1, have multiple substrates in vivo, which are often transcriptional regulators. However, S2Ps will also cleave transmembrane sequences of nonsubstrate proteins, suggesting additional specificity determinants. Many S2Ps also contain a PDZ domain, the function of which is poorly understood. Here, we identify an M. tuberculosis protein, PDZ-interacting protease regulator 1 (Ppr1), which bridges between the Rip1 PDZ domain and anti-sigma factor M (Anti-SigM), a Rip1 substrate, but not Anti-SigK or Anti-SigL, also Rip1 substrates. In vivo analyses of Ppr1 function indicate that it prevents nonspecific activation of the Rip1 pathway while coupling Rip1 cleavage of Anti-SigM, but not Anti-SigL, to site-1 proteolysis. Our results support a model of S2P substrate specificity in which a substrate-specific adapter protein tethers the S2P to its substrate while holding the protease inactive through its PDZ domain.

Noninvasive Imaging of PSMA in prostate tumors with (89)Zr-Labeled huJ591 engineered antibody fragments: the faster alternatives.

Engineered antibody fragments offer faster delivery with retained tumor specificity and rapid clearance from nontumor tissues. Here, we demonstrate that positron emission tomography (PET) based detection of prostate specific membrane antigen (PSMA) in prostatic tumor models using engineered bivalent antibodies built on single chain fragments (scFv) derived from the intact antibody, huJ591, offers similar tumor delineating properties but with the advantage of rapid targeting and imaging. (89)Zr-radiolabeled huJ591 scFv (dimeric scFv-CH3; (89)Zr-Mb) and cysteine diabodies (dimeric scFv; (89)Zr-Cys-Db) demonstrated internalization and similar Kds (∼2 nM) compared to (89)Zr-huJ591 in PSMA(+) cells. Tissue distribution assays established the specificities of both (89)Zr-Mb and (89)Zr-Cys-Db for PSMA(+) xenografts (6.2 ± 2.5% ID/g and 10.2 ± 3.4% ID/g at 12 h p.i. respectively), while minimal accumulation in PSMA(-) tumors was observed. From the PET images, (89)Zr-Mb and (89)Zr-Cys-Db exhibited faster blood clearance than the parent huJ591 while tumor-to-muscle ratios for all probes show comparable values across all time points. Ex vivo autoradiography and histology assessed the distribution of the probes within the tumor. Imaging PSMA-expressing prostate tumors with smaller antibody fragments offers rapid tumor accumulation and accelerated clearance; hence, shortened wait periods between tracer administration and high-contrast tumor imaging and lower dose-related toxicity are potentially realized.

Acceptability of electronic healthcare predictive analytics for HIV prevention: a qualitative study with men who have sex with men in New York City.

BACKGROUND: Large data sets, also known as "big data", shared in health information exchanges (HIEs), can be used in novel ways to advance health, including among communities at risk for HIV infection. We examined values and opinions about the acceptability of using electronic healthcare predictive analytics (eHPA) to promote HIV prevention in men who have sex with men (MSM). Our aims were twofold: (I) to evaluate the perspectives of MSM with diverse race/ethnicity and age on the acceptability of predictive analytics to determine individual HIV risk and (II) to determine acceptability of having targeted prevention messaging based upon those risk estimates sent directly to the consumer.Method: Two of the authors facilitated 12 focus groups (n=57) with adult MSM without HIV, living in NYC. Groups were divided by ethnicity (Black, Latino, and White) and age (under 35 and 35 and over). Participants were recruited through HIV prevention sites, community-based organizations, social media, and Internet sites that serve these communities. Grounded theory methods were used to analyze the data with Dedoose. RESULTS: We identified six main themes related to acceptability: (I) reach, relevance, and potential uptake of using predictive analytics to establish HIV risk and deliver targeted prevention messaging; (II) patient-provider communication; (III) public health and individual rights; (IV) perceptions of intervention effectiveness; (V) electronic health data security; and (VI) stigma. Within each thematic domain, MSM discussed concerns, benefits, and provided recommendations for implementation. CONCLUSIONS: MSM in this study were supportive of the use of "big data" and technology to reach marginalized populations and improve public health, yet expressed concerns about the relevance, effectiveness, and security eHPA. Efforts to advance eHPA for HIV prevention should address these concerns, especially among the most-at-risk communities of color. Development of eHPA for HIV prevention should involve targeted messaging that addresses specific concerns regarding eHPA security, accuracy, and relevance.

Development and Validation of an Electronic Medical Record-Based Algorithm to Identify Patient Milestones in the Hepatitis C Virus Care Cascade.

Disease-specific care cascades are important public health and organizational tools to characterize gaps in care and target resources, but they are labor-intensive to maintain. Using data available from the electronic medical record, we developed an algorithm with high accuracy for correctly representing an individual's status in the hepatitis C virus care cascade.

Towards the Inference of Social and Behavioral Determinants of Sexual Health: Development of a Gold-Standard Corpus with Semi-Supervised Learning.

Social and behavioral determinants of health (SBDH) are environmental and behavioral factors that are increasingly recognized for their impact on health outcomes. We describe ongoing research to extract SBDH related to sexual health from clinical documentation. Our work addresses several challenges. First, there is no standard set of SBDHs for sexual health; we describe our curation of 38 such SBDHs. Second, it is unknown how SBDH related to sexual health are expressed in clinical notes; we detail the characteristics of an annotated corpus. Third, SBDH documentations are rare; we describe the use of semi-supervised learning to accelerate the annotation process by identifying notes likely to document SBDH. Fourth, we describe preliminary results to infer an array of SBDH from clinical documentation using supervised learning.