Exploring Indonesian actinomycete extracts for anti-tubercular compounds: Integrating inhibition assessment, genomic analysis, and prediction of its target by molecular docking.

Tuberculosis (TB) is the foremost cause of infectious fatality globally. The primary global challenge in combatting TB lies in addressing the emergence of drug-resistant variants of the disease. However, the number of newly approved agents for treating TB has remained remarkably low over recent decades. Hence, research endeavors for discovering novel anti-TB agents are always needed. In the present study, we screened over 1,500 culture extracts from actinomycetes isolated in Indonesia for their inhibitory activity against Mycobacterium smegmatis used as a surrogate in the primary screening. The initial screening yielded approximately 6.2 % hit extracts, with a selection criterion of >80 % growth inhibition. The confirmed hit extracts were subsequently subjected to growth inhibition assay against Mycobacterium bovis and Mycobacterium tuberculosis. Approximately 20 % of the hit extracts that showed growth inhibition also exhibited efficacy against M. bovis BCG and M. tuberculosis H37Rv pathogenic strain. An active compound was successfully purified from a large-scale culture of the most potent representative extract by high-performance liquid chromatography and thin-layer chromatography. The structure of the active compound was elucidated by mass spectrometry and nuclear magnetic resonance. This compound displayed structural similarities to actinomycin group and exhibited robust inhibition, with IC50 values of 0.74, 0.02, and 0.07 µg/mL against M. smegmatis, M. bovis, and M. tuberculosis, respectively. The Actinomycetes strain A612, which produced the active compound, was taxonomically classified by phylogenetic analysis of 16s rRNA gene and whole genome sequencing data as Streptomyces parvus. Computational genome analysis utilizing anti-SMASH 7.0 unveiled that S. parvus A612 strain harbors 40 biosynthetic gene clusters with the potential to produce 16 known (with >70 % similarity) and 24 unknown compounds. A non-ribosomal peptide synthesis (NRPS) gene cluster associated with actinomycin D biosynthesis was also identified, boasting an 85 % similarity. Molecular docking analysis of actinomycin D and 21 potential M. tuberculosis targets revealed possible interactions with multiple targets. The purified active compound inhibited recombinant M. tuberculosis shikimate kinase (MtSK), which validated the results obtained from the docking analysis.

The dynamics of circulating SARS-CoV-2 lineages in Bogor and surrounding areas reflect variant shifting during the first and second waves of COVID-19 in Indonesia.

Background: Indonesia is one of the Southeast Asian countries with high case numbers of COVID-19 with up to 4.2 million confirmed cases by 29 October 2021. Understanding the genome of SARS-CoV-2 is crucial for delivering public health intervention as certain variants may have different attributes that can potentially affect their transmissibility, as well as the performance of diagnostics, vaccines, and therapeutics. Objectives: We aimed to investigate the dynamics of circulating SARS-CoV-2 variants over a 15-month period in Bogor and its surrounding areas in correlation with the first and second wave of COVID-19 in Indonesia. Methods: Nasopharyngeal and oropharyngeal swab samples collected from suspected patients from Bogor, Jakarta and Tangerang were confirmed for SARS-CoV-2 infection with RT-PCR. RNA samples of those confirmed patients were subjected to whole genome sequencing using the ARTIC Network protocol and sequencer platform from Oxford Nanopore Technologies (ONT). Results: We successfully identified 16 lineages and six clades out of 202 samples (male n = 116, female n = 86). Genome analysis revealed that Indonesian lineage B.1.466.2 dominated during the first wave (n = 48, 23.8%) while Delta variants (AY.23, AY.24, AY.39, AY.42, AY.43 dan AY.79) were dominant during the second wave (n = 53, 26.2%) following the highest number of confirmed cases in Indonesia. In the spike protein gene, S_D614G and S_P681R changes were dominant in both B.1.466.2 and Delta variants, while N439K was only observed in B.1.466.2 (n = 44) and B.1.470 (n = 1). Additionally, the S_T19R, S_E156G, S_F157del, S_R158del, S_L452R, S_T478K, S_D950N and S_V1264L changes were only detected in Delta variants, consistent with those changes being characteristic of Delta variants in general. Conclusions: We demonstrated a shift in SARS-CoV-2 variants from the first wave of COVID-19 to Delta variants in the second wave, during which the number of confirmed cases surpassed those in the first wave of COVID-19 pandemic. Higher proportion of unique mutations detected in Delta variants compared to the first wave variants indicated potential mutational effects on viral transmissibility that correlated with a higher incidence of confirmed cases. Genomic surveillance of circulating variants, especially those with higher transmissibility, should be continuously conducted to rapidly inform decision making and support outbreak preparedness, prevention, and public health response.

Self-Assembled Behavior of Ultralightweight Aerogel from a Mixture of CNC/CNF from Oil Palm Empty Fruit Bunches.

This study aims to explore the use of cellulose nanocrystals (CNC) and cellulose nanofiber (CNF), obtained from unbleached fiber of oil palm empty fruit bunches (EFB), as raw materials in fabricating aerogel, using the facile technique without solvent displacement. The CNC was isolated from sulfuric acid hydrolysis, and the CNF was fibrillated using Ultra Turrax. The CNC and CNF were mixed by ultrasonication in different ratios to produce aerogel using slow freezing (-20 °C), followed by freeze-drying. The obtained aerogel was characterized as ultralightweight and highly porous material, at the density range of 0.0227 to 0.0364 g/cm3 and porosity of 98.027 to 98.667%. Interestingly, the ratio of CNC and CNF significantly affected the characteristics of the obtained aerogel. The mixed aerogel exhibited a higher specific surface area than pure CNC or CNF, with the highest value of 202.72 m2/g for the ratio of 1:3 (CNC/CNF). In addition, the crystallinity degree of obtained aerogel showed a higher value in the range of 76.49 to 69.02%, with the highest value being obtained for higher CNC content. This study is expected to provide insight into nanocellulose-based aerogel, with a promising potential for various applications.