DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model.

Continuous blood pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitored using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introduce a blood pressure monitoring algorithm based on only photoplethysmography (PPG) signals using the deep neural network (DNN). The PPG signals are obtained from 125 unique subjects with 218 records and filtered using signal processing algorithms to reduce the effects of noise, such as baseline wandering, and motion artifacts. The proposed algorithm is based on pulse wave analysis of PPG signals, extracted various domain features from PPG signals, and mapped them to BP values. Four feature selection methods are applied and yielded four feature subsets. Therefore, an ensemble feature selection technique is proposed to obtain the optimal feature set based on major voting scores from four feature subsets. DNN models, along with the ensemble feature selection technique, outperformed in estimating the systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to previously reported approaches that rely only on the PPG signal. The coefficient of determination ( R 2 ) and mean absolute error (MAE) of the proposed algorithm are 0.962 and 2.480 mmHg, respectively, for SBP and 0.955 and 1.499 mmHg, respectively, for DBP. The proposed approach meets the Advancement of Medical Instrumentation standard for SBP and DBP estimations. Additionally, according to the British Hypertension Society standard, the results attained Grade A for both SBP and DBP estimations. It concludes that BP can be estimated more accurately using the optimal feature set and DNN models. The proposed algorithm has the potential ability to facilitate mobile healthcare devices to monitor continuous BP.

Bridging Communication Gaps: A Study on Effective Patient Communication Among Respiratory Therapy Students and Interns.

Introduction Effective communication in healthcare plays a pivotal role, significantly impacting patient experiences and outcomes. While much of the current literature focuses on communication dynamics among physicians and nurses, a gap exists in understanding these dynamics within allied health professions such as respiratory therapy. This study explores the knowledge, attitudes, and awareness of patient communication among respiratory therapy students and interns. Methods This descriptive cross-sectional study investigated the knowledge, attitudes, and awareness of effective communication methods with patients among respiratory therapy students and interns in Jeddah, Saudi Arabia. Using a validated self-administered questionnaire, the study surveyed 350 individuals from three universities and associated hospitals. Results The analysis involved 350 participants, with females comprising 55.1%. The study found that the highest level of agreement (mean 4.6±0.62) was regarding essential knowledge related to introducing respiratory therapists to patients during communication. Female students demonstrated significant proficiency in concluding patient interviews (P=0.033), while male students excelled in comprehending communication methods with unconscious patients (P=0.010). Interns exhibited the most comprehensive understanding of patient communication skills, particularly in employing open-ended questions (P=0.009) and allowing adequate time for patients to express their concerns (P=0.020). Gender and academic progression were identified as factors influencing patient communication skills in respiratory therapy students and interns. Conclusion This study highlights the need for tailored communication training for respiratory therapy students and interns. It emphasizes the importance of enhancing proficiency in this vital field by addressing knowledge gaps and identifying areas for improvement.

Navigating Virtual Learning Landscapes: Perspectives of Health Sciences Students in Saudi Arabia During the COVID-19 Pandemic.

Introduction In December 2019, COVID-19 originated in Wuhan, China, triggering a global pandemic. However, the Saudi Arabian Ministry of Education ensured the safe continuation of teaching and learning activities. Amid the pandemic, health sciences students were exposed to diverse learning opportunities. Methods This study seeks to explore their experiences with online teaching. Conducted as a descriptive cross-sectional study, it involved 397 health sciences students from three universities in the Makkah province who had encountered both traditional and virtual teaching methods. Results Most participants were female (71.1%), predominantly from Jeddah city (76.5%). The highest agreement scores were observed for student comprehension during online sessions (61.1%). A significant proportion (74.4%) found paying attention during online lectures easier than traditional ones. Blackboard emerged as the preferred educational platform for online teaching. Notably, there were no significant variations in students' perceptions of online teaching based on location, gender, or specialisation. Approximately 54.7% of students preferred watching their instructors through a webcam during online lectures. Conclusion Medical educators can leverage these findings to develop standardised teaching protocols and enhance the effectiveness of online education systems. The study underscores the importance of instructors using webcams during online teaching sessions, as it allows students to visually connect with their instructors, potentially improving the learning experience.

Antimycobacterial and healing effects of Pranlukast against MTB infection and pathogenesis in a preclinical mouse model of tuberculosis.

It is essential to understand the interactions and relationships between Mycobacterium tuberculosis (Mtb) and macrophages during the infection in order to design host-directed, immunomodulation-dependent therapeutics to control Mtb. We had reported previously that ornithine acetyltransferase (MtArgJ), a crucial enzyme of the arginine biosynthesis pathway of Mtb, is allosterically inhibited by pranlukast (PRK), which significantly reduces bacterial growth. The present investigation is centered on the immunomodulation in the host by PRK particularly the activation of the host's immune response to counteract bacterial survival and pathogenicity. Here, we show that PRK decreased the bacterial burden in the lungs by upregulating the population of pro-inflammatory interstitial macrophages (IMs) and reducing the population of Mtb susceptible alveolar macrophages (AMs), dendritic cells (DCs), and monocytes (MO). Additionally, we deduce that PRK causes the host macrophages to change their metabolic pathway from fatty acid metabolism to glycolytic metabolism around the log phage of bacterial multiplication. Further, we report that PRK reduced tissue injury by downregulating the Ly6C-positive population of monocytes. Interestingly, PRK treatment improved tissue repair and inflammation resolution by increasing the populations of arginase 1 (Arg-1) and Ym1+Ym2 (chitinase 3-like 3) positive macrophages. In summary, our study found that PRK is useful not only for reducing the tubercular burden but also for promoting the healing of the diseased tissue.

A continuous cuffless blood pressure measurement from optimal PPG characteristic features using machine learning algorithms.

Background and objective: Hypertension is a potentially dangerous health condition that can be detected by measuring blood pressure (BP). Blood pressure monitoring and measurement are essential for preventing and treating cardiovascular diseases. Cuff-based devices, on the other hand, are uncomfortable and prevent continuous BP measurement. Methods: In this study, a new non-invasive and cuff-less method for estimating Systolic Blood Pressure (SBP), Mean Arterial Pressure (MAP), and Diastolic Blood Pressure (DBP) has been proposed using characteristic features of photoplethysmogram (PPG) signals and nonlinear regression algorithms. PPG signals were collected from 219 participants, which were then subjected to preprocessing and feature extraction steps. Analyzing PPG and its derivative signals, a total of 46 time, frequency, and time-frequency domain features were extracted. In addition, the age and gender of each subject were also included as features. Further, correlation-based feature selection (CFS) and Relief F feature selection (ReliefF) techniques were used to select the relevant features and reduce the possibility of over-fitting the models. Finally, support vector regression (SVR), K-nearest neighbour regression (KNR), decision tree regression (DTR), and random forest regression (RFR) were established to develop the BP estimation model. Regression models were trained and evaluated on all features as well as selected features. The best regression models for SBP, MAP, and DBP estimations were selected separately. Results: The SVR model, along with the ReliefF-based feature selection algorithm, outperforms other algorithms in estimating the SBP, MAP, and DBP with the mean absolute error of 2.49, 1.62 and 1.43 mmHg, respectively. The proposed method meets the Advancement of Medical Instrumentation standard for BP estimations. Based on the British Hypertension Society standard, the results also fall within Grade A for SBP, MAP, and DBP. Conclusion: The findings show that the method can be used to estimate blood pressure non-invasively, without using a cuff or calibration, and only by utilizing the PPG signal characteristic features.

Contribution of infection and vaccination to population-level seroprevalence through two COVID waves in Tamil Nadu, India.

This study employs repeated, large panels of serological surveys to document rapid and substantial waning of SARS-CoV-2 antibodies at the population level and to calculate the extent to which infection and vaccination separately contribute to seroprevalence estimates. Four rounds of serological surveys were conducted, spanning two COVID waves (October 2020 and April-May 2021), in Tamil Nadu (population 72 million) state in India. Each round included representative populations in each district of the state, totaling ≥ 20,000 persons per round. State-level seroprevalence was 31.5% in round 1 (October-November 2020), after India's first COVID wave. Seroprevalence fell to 22.9% in round 2 (April 2021), a roughly one-third decline in 6 months, consistent with dramatic waning of SARS-Cov-2 antibodies from natural infection. Seroprevalence rose to 67.1% by round 3 (June-July 2021), with infections from the Delta-variant induced second COVID wave accounting for 74% of the increase. Seroprevalence rose to 93.1% by round 4 (December 2021-January 2022), with vaccinations accounting for 63% of the increase. Antibodies also appear to wane after vaccination. Seroprevalence in urban areas was higher than in rural areas, but the gap shrunk over time (35.7 v. 25.7% in round 1, 89.8% v. 91.4% in round 4) as the epidemic spread even in low-density rural areas.

Action-outcome delays modulate the temporal expansion of intended outcomes.

The phenomenon of intentional binding pertains to the perceived connection between a voluntary action and its anticipated result. When an individual intends an outcome, it appears to subjectively extend in time due to a pre-activation of the intended result, particularly evident at shorter action-outcome delays. However, there is a concern that the operationalisation of intention might have led to a mixed interpretation of the outcome expansion attributed to the pre-activation of intention, given the sensitivity of time perception and intentional binding to external cues that could accelerate the realisation of expectations. To investigate the expansion dynamics of an intended outcome, we employed a modified version of the temporal bisection task in two experiments. Experiment 1 considered the action-outcome delay as a within-subject factor, while experiment 2 treated it as a between-subject factor. The results revealed that the temporal expansion of an intended outcome was only evident under the longer action-outcome delay condition. We attribute this observation to working memory demands and attentional allocation due to temporal relevancy and not due to pre-activation. The discrepancy in effects across studies is explained by operationalising different components of the intentional binding effect, guided by the cue integration theory. Moreover, we discussed speculative ideas regarding the involvement of specific intentions based on the proximal intent distal intent (PIDI) theory and whether causality plays a role in temporal binding. Our study contributes to the understanding of how intention influences time perception and sheds light on how various methodological factors, cues, and delays can impact the dynamics of temporal expansion associated with an intended outcome.

Attention-based fusion of multiple graphheat networks for structural to functional brain mapping.

Over the last decade, there has been growing interest in learning the mapping from structural connectivity (SC) to functional connectivity (FC) of the brain. The spontaneous fluctuations of the brain activity during the resting-state as captured by functional MRI (rsfMRI) contain rich non-stationary dynamics over a relatively fixed structural connectome. Among the modeling approaches, graph diffusion-based methods with single and multiple diffusion kernels approximating static or dynamic functional connectivity have shown promise in predicting the FC given the SC. However, these methods are computationally expensive, not scalable, and fail to capture the complex dynamics underlying the whole process. Recently, deep learning methods such as GraphHeat networks and graph diffusion have been shown to handle complex relational structures while preserving global information. In this paper, we propose a novel attention-based fusion of multiple GraphHeat networks (A-GHN) for mapping SC-FC. A-GHN enables us to model multiple heat kernel diffusion over the brain graph for approximating the complex Reaction Diffusion phenomenon. We argue that the proposed deep learning method overcomes the scalability and computational inefficiency issues but can still learn the SC-FC mapping successfully. Training and testing were done using the rsfMRI data of 1058 participants from the human connectome project (HCP), and the results establish the viability of the proposed model. On HCP data, we achieve a high Pearson correlation of 0.788 (Desikan-Killiany atlas with 87 regions) and 0.773 (AAL atlas with 86 regions). Furthermore, experiments demonstrate that A-GHN outperforms the existing methods in learning the complex nature of the structure-function relation of the human brain.

MicroRNA-22-3p displaces critical host factors from the 5' UTR and inhibits the translation of Coxsackievirus B3 RNA.

Coxsackievirus B3 (CVB3) is known to cause acute myocarditis and pancreatitis in humans. We investigated the microRNAs (miRNAs) that can potentially govern the viral life cycle by binding to the untranslated regions (UTRs) of CVB3 RNA. MicroRNA-22-3p was short-listed, as its potential binding site overlapped with the region crucial for recruiting internal ribosome entry site trans-acting factors (ITAFs) and ribosomes. We demonstrate that miR-22-3p binds CVB3 5' UTR, hinders recruitment of key ITAFs on viral mRNA, disrupts the spatial structure required for ribosome recruitment, and ultimately blocks translation. Likewise, cells lacking miR-22-3p exhibited heightened CVB3 infection compared to wild type, confirming its role in controlling infection. Interestingly, miR-22-3p level was found to be increased at 4 hours post-infection, potentially due to the accumulation of viral 2A protease in the early phase of infection. 2Apro enhances the miR-22-3p level to dislodge the ITAFs from the SD-like sequence, rendering the viral RNA accessible for binding of replication factors to switch to replication. Furthermore, one of the cellular targets of miR-22-3p, protocadherin-1 (PCDH1), was significantly downregulated during CVB3 infection. Partial silencing of PCDH1 reduced viral replication, demonstrating its proviral role. Interestingly, upon CVB3 infection in mice, miR-22-3p level was found to be downregulated only in the small intestine, the primary target organ, indicating its possible role in influencing tissue tropism. It appears miR-22-3p plays a dual role during infection by binding viral RNA to aid its life cycle as a viral strategy and by targeting a proviral protein to restrict viral replication as a host response.IMPORTANCECVB3 infection is associated with the development of end-stage heart diseases. Lack of effective anti-viral treatments and vaccines for CVB3 necessitates comprehensive understanding of the molecular players during CVB3 infection. miRNAs have emerged as promising targets for anti-viral strategies. Here, we demonstrate that miR-22-3p binds to 5' UTR and inhibits viral RNA translation at the later stage of infection to promote viral RNA replication. Conversely, as host response, it targets PCDH1, a proviral factor, to discourage viral propagation. miR-22-3p also influences CVB3 tissue tropism. Deciphering the multifaced role of miR-22-3p during CVB3 infection unravels the necessary molecular insights, which can be exploited for novel intervening strategies to curb infection and restrict viral pathogenesis.

Challenges and Opportunities for Commercializing Technologies in the Pulmonary Arena: An Official American Thoracic Society Report.

"Translational medicine" has been a buzzword for over two decades. The concept was intended to be lofty, to reflect a new "bench-to-bedside" approach to basic and clinical research that would bridge fields, close gaps, accelerate innovation, and shorten the time and effort it takes to bring novel technologies from basic discovery to clinical application. Has this approach been successful and lived up to its promise? Despite incredible scientific advances and innovations developed within academia, successful clinical translation into real-world solutions has been difficult. This has been particularly challenging within the pulmonary field, because there have been fewer U.S. Food and Drug Administration-approved drugs and higher failure rates for pulmonary therapies than with other common disease areas. The American Thoracic Society convened a working group with the goal of identifying major challenges related to the commercialization of technologies within the pulmonary space and opportunities to enhance this process. A survey was developed and administered to 164 participants within the pulmonary arena. This report provides a summary of these survey results. Importantly, this report identifies a number of poorly recognized challenges that exist in pulmonary academic settings, which likely contribute to diminished efficiency of commercialization efforts, ultimately hindering the rate of successful clinical translation. Because many innovations are initially developed in academic settings, this is a global public health issue that impacts the entire American Thoracic Society community. This report also summarizes key resources and opportunities and provides recommendations to enhance successful commercialization of pulmonary technologies.

Cysteine desulfurase (IscS)-mediated fine-tuning of bioenergetics and SUF expression prevents Mycobacterium tuberculosis hypervirulence.

Iron-sulfur (Fe-S) biogenesis requires multiprotein assembly systems, SUF and ISC, in most prokaryotes. M. tuberculosis (Mtb) encodes a complete SUF system, the depletion of which was bactericidal. The ISC operon is truncated to a single gene iscS (cysteine desulfurase), whose function remains uncertain. Here, we show that MtbΔiscS is bioenergetically deficient and hypersensitive to oxidative stress, antibiotics, and hypoxia. MtbΔiscS resisted killing by nitric oxide (NO). RNA sequencing indicates that IscS is important for expressing regulons of DosR and Fe-S-containing transcription factors, WhiB3 and SufR. Unlike wild-type Mtb, MtbΔiscS could not enter a stable persistent state, continued replicating in mice, and showed hypervirulence. The suf operon was overexpressed in MtbΔiscS during infection in a NO-dependent manner. Suppressing suf expression in MtbΔiscS either by CRISPR interference or upon infection in inducible NO-deficient mice arrests hypervirulence. Together, Mtb redesigned the ISC system to "fine-tune" the expression of SUF machinery for establishing persistence without causing detrimental disease in the host.

Enhancing Immunogenicity of a Thermostable, Efficacious SARS-CoV-2 Vaccine Formulation through Oligomerization and Adjuvant Choice.

Currently deployed SARS-CoV-2 vaccines all require storage at refrigerated or sub-zero temperatures. We demonstrate that after month-long incubation at 37 °C, solubilization, and formulation with squalene-in-water emulsion adjuvant, a stabilized receptor binding domain retains immunogenicity and protective efficacy. We also examine the effects of trimerization of the stabilized RBD, as well as of additional adjuvants, on both B and T-cell responses. The additional emulsion or liposome-based adjuvants contained a synthetic TLR-4 ligand and/or the saponin QS-21. Trimerization enhanced immunogenicity, with significant antibody titers detectable after a single immunization. Saponin-containing adjuvants elicited enhanced immunogenicity relative to both emulsion and aluminum hydroxide adjuvanted formulations lacking these immunostimulants. Trimeric RBD formulated with liposomal based adjuvant containing both TLR-4 ligand and saponin elicited a strongly Th1 biased response, with ~10-fold higher neutralization titers than the corresponding aluminum hydroxide adjuvanted formulation. The SARS-CoV-2 virus is now endemic in humans, and it is likely that periodic updating of vaccine formulations in response to viral evolution will continue to be required to protect vulnerable individuals. In this context, it is desirable to have efficacious, thermostable vaccine formulations to facilitate widespread vaccine coverage, including in low- and middle-income countries, where global access rights to clinically de-risked adjuvants will be important moving forward.

The Mycobacterium tuberculosis methyltransferase Rv2067c manipulates host epigenetic programming to promote its own survival.

Mycobacterium tuberculosis has evolved several mechanisms to counter host defense arsenals for its proliferation. Here we report that M. tuberculosis employs a multi-pronged approach to modify host epigenetic machinery for its survival. It secretes methyltransferase (MTase) Rv2067c into macrophages, trimethylating histone H3K79 in a non-nucleosomal context. Rv2067c downregulates host MTase DOT1L, decreasing DOT1L-mediated nucleosomally added H3K79me3 mark on pro-inflammatory response genes. Consequent inhibition of caspase-8-dependent apoptosis and enhancement of RIPK3-mediated necrosis results in increased pathogenesis. In parallel, Rv2067c enhances the expression of SESTRIN3, NLRC3, and TMTC1, enabling the pathogen to overcome host inflammatory and oxidative responses. We provide the structural basis for differential methylation of H3K79 by Rv2067c and DOT1L. The structures of Rv2067c and DOT1L explain how their action on H3K79 is spatially and temporally separated, enabling Rv2067c to effectively intercept the host epigenetic circuit and downstream signaling.

Comparative genomics of the niche-specific plant pathogen Streptomyces ipomoeae reveal novel genome content and organization.

IMPORTANCE: While most plant-pathogenic Streptomyces species cause scab disease on a variety of plant hosts, Streptomyces ipomoeae is the sole causative agent of soil rot disease of sweet potato and closely related plant species. Here, genome sequencing of virulent and avirulent S. ipomoeae strains coupled with comparative genomic analyses has identified genome content and organization features unique to this streptomycete plant pathogen. The results here will enable future research into the mechanisms used by S. ipomoeae to cause disease and to persist in its niche environment.

G9a and Sirtuin6 epigenetically modulate host cholesterol accumulation to facilitate mycobacterial survival.

Cholesterol derived from the host milieu forms a critical factor for mycobacterial pathogenesis. However, the molecular circuitry co-opted by Mycobacterium tuberculosis (Mtb) to accumulate cholesterol in host cells remains obscure. Here, we report that the coordinated action of WNT-responsive histone modifiers G9a (H3K9 methyltransferase) and SIRT6 (H3K9 deacetylase) orchestrate cholesterol build-up in in vitro and in vivo mouse models of Mtb infection. Mechanistically, G9a, along with SREBP2, drives the expression of cholesterol biosynthesis and uptake genes; while SIRT6 along with G9a represses the genes involved in cholesterol efflux. The accumulated cholesterol in Mtb infected macrophages promotes the expression of antioxidant genes leading to reduced oxidative stress, thereby supporting Mtb survival. In corroboration, loss-of-function of G9a in vitro and pharmacological inhibition in vivo; or utilization of BMDMs derived from Sirt6-/- mice or in vivo infection in haplo-insufficient Sirt6-/+ mice; hampered host cholesterol accumulation and restricted Mtb burden. These findings shed light on the novel roles of G9a and SIRT6 during Mtb infection and highlight the previously unknown contribution of host cholesterol in potentiating anti-oxidative responses for aiding Mtb survival.

Directing the Stereoselectivity of the Claisen Rearrangement to Form Cyclic Ketones with Full Substitution at the α-Positions.

We report an enantioselective synthesis of cyclic ketones with full substitutions at the α-positions in a highly diastereoselective manner. Our method is achieved by subjecting substrate motifs in 2-allyloxyenones to chiral organomagnesium reagents, which trigger the Claisen rearrangement upon direct 1,2-carbonyl addition. The observed diastereoselectivity of the allyl migration is proposed to originate from the intramolecular chelation of the magnesium alkoxide to the allyloxy moiety.

Enhanced protective efficacy of a thermostable RBD-S2 vaccine formulation against SARS-CoV-2 and its variants.

With the rapid emergence of variants of concern (VOC), the efficacy of currently licensed vaccines has reduced drastically. VOC mutations largely occur in the S1 subunit of Spike. The S2 subunit of SARS-CoV-2 is conserved and thus more likely to elicit broadly reactive immune responses that could improve protection. However, the contribution of the S2 subunit in improving the overall efficacy of vaccines remains unclear. Therefore, we designed, and evaluated the immunogenicity and protective potential of a stabilized SARS-CoV-2 Receptor Binding Domain (RBD) fused to a stabilized S2. Immunogens were expressed as soluble proteins with approximately fivefold higher purified yield than the Spike ectodomain and formulated along with Squalene-in-water emulsion (SWE) adjuvant. Immunization with S2 alone failed to elicit a neutralizing immune response, but significantly reduced lung viral titers in mice challenged with the heterologous Beta variant. In hamsters, SWE-formulated RS2 (a genetic fusion of stabilized RBD with S2) showed enhanced immunogenicity and efficacy relative to corresponding RBD and Spike formulations. Despite being based on the ancestral Wuhan strain of SARS-CoV-2, RS2 elicited broad neutralization, including against Omicron variants (BA.1, BA.5 and BF.7), and the clade 1a WIV-1 and SARS-CoV-1 strains. RS2 elicited sera showed enhanced competition with both S2 directed and RBD Class 4 directed broadly neutralizing antibodies, relative to RBD and Spike elicited sera. When lyophilized, RS2 retained antigenicity and immunogenicity even after incubation at 37 °C for a month. The data collectively suggest that the RS2 immunogen is a promising modality to combat SARS-CoV-2 variants.

PARP1 inhibition protects mice against Japanese encephalitis virus infection.

Japanese encephalitis (JE) is a vector-borne viral disease that causes acute encephalitis in children. Although vaccines have been developed against the JE virus (JEV), no effective antiviral therapy exists. Our study shows that inhibition of poly(ADP-ribose) polymerase 1 (PARP1), an NAD+-dependent (poly-ADP) ribosyl transferase, protects against JEV infection. Interestingly, PARP1 is critical for JEV pathogenesis in Neuro-2a cells and mice. Small molecular inhibitors of PARP1, olaparib, and 3-aminobenzamide (3-AB) significantly reduce clinical signs and viral load in the serum and brains of mice and improve survival. PARP1 inhibition confers protection against JEV infection by inhibiting autophagy. Mechanistically, upon JEV infection, PARP1 PARylates AKT and negatively affects its phosphorylation. In addition, PARP1 transcriptionally upregulates PTEN, the PIP3 phosphatase, negatively regulating AKT. PARP1-mediated AKT inactivation promotes autophagy and JEV pathogenesis by increasing the FoxO activity. Thus, our findings demonstrate PARP1 as a potential mediator of JEV pathogenesis that can be effectively targeted for treating JE.

Biosensor-integrated transposon mutagenesis reveals rv0158 as a coordinator of redox homeostasis in Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) is evolutionarily equipped to resist exogenous reactive oxygen species (ROS) but shows vulnerability to an increase in endogenous ROS (eROS). Since eROS is an unavoidable consequence of aerobic metabolism, understanding how Mtb manages eROS levels is essential yet needs to be characterized. By combining the Mrx1-roGFP2 redox biosensor with transposon mutagenesis, we identified 368 genes (redoxosome) responsible for maintaining homeostatic levels of eROS in Mtb. Integrating redoxosome with a global network of transcriptional regulators revealed a hypothetical protein (Rv0158) as a critical node managing eROS in Mtb. Disruption of rv0158 (rv0158 KO) impaired growth, redox balance, respiration, and metabolism of Mtb on glucose but not on fatty acids. Importantly, rv0158 KO exhibited enhanced growth on propionate, and the Rv0158 protein directly binds to methylmalonyl-CoA, a key intermediate in propionate catabolism. Metabolite profiling, ChIP-Seq, and gene-expression analyses indicate that Rv0158 manages metabolic neutralization of propionate toxicity by regulating the methylcitrate cycle. Disruption of rv0158 enhanced the sensitivity of Mtb to oxidative stress, nitric oxide, and anti-TB drugs. Lastly, rv0158 KO showed poor survival in macrophages and persistence defect in mice. Our results suggest that Rv0158 is a metabolic integrator for carbon metabolism and redox balance in Mtb.