Biology subjects

Uhlemann, A.-C.

Publications and source records attributed to Uhlemann, A.-C..

18 recordsLinked to original sources

bioRxiv2026

Interconnected reservoirs of multidrug-resistant bacteria and plasmids within the hospital built environment

Hospital sinks and wastewater streams are hotspots for contamination and colonization with multidrug-resistant Gram-negative bacteria (MDR-GNB). However, longitudinal studies investigating the population dynamics of environmental MDR-GNB and links between patients and the environment are lacking, especially in non-outbreak settings. Here we aimed to characterize the diversity and abundance of MDR-GNB across the hospital built environment and evaluate their relationship with clinical isolates. We performed nanopore sequencing on MDR-GNB cultured from sink drains (n=523) and wastewater (n=146) at a New York City hospital between March-August 2023. Using comparative genomics and plasmid clustering analyses, we assessed spatial and longitudinal strain and plasmid dynamics and quantified relatedness to historical clinical isolates from the same hospital (n=602). Sink drains (54-73%) and wastewater (100%) demonstrated widespread, longitudinal colonization with MDR-GNB, driven primarily by carbapenem-resistant GNB including opportunistic organisms and Enterobacterales encoding blaKPC. While bacterial colonization was largely niche-specific, we identified both MDR-GNB strains and resistance plasmids that were shared between clinical and environmental sources, as well as differing dynamics between clinical and wastewater versus sink drain samples. This study supports the role of the hospital environment as an important reservoir for clinically-relevant MDR-GNB, but highlights differences across environmental sites which may impact surveillance approaches.

microbiology↗

bioRxiv2026

Double Mutations in Plasmodium falciparum Kelch13 drive resistance to next-generation artemisinin derivatives in malaria parasites

New antimalarial compounds are urgently required to overcome artemisinin partial resistance that has emerged in Asia and now Africa. Ozonides are promising next-generation artemisinins that offer the improved pharmacokinetic property of a prolonged in vivo half-life. To assess the potential for parasite resistance to ozonides in an artemisinin-resistant background, we subjected Cambodian Kelch13 (K13) mutant parasites to increasing artefenomel (OZ439) pressure up to in vivo physiological concentrations. Whole-genome sequencing identified a novel non-propeller K13 A212T mutation in OZ439-resistant parasites. Gene editing and drug susceptibility assays revealed that the K13 double mutation R539T+A212T is a determinant of OZ439 resistance. In extended parasite recovery assays, this resistance mechanism was associated with accelerated parasite recrudescence following OZ439 or OZ277 exposure. This phenotype was also observed in K13 C580Y+A212T double mutant parasites. Global metabolomic profiling revealed no changes in the levels of hemoglobin-derived peptides in OZ439-resistant parasites, suggesting that resistance is not associated with drug activation. Instead, double mutant parasites exhibited increased levels of metabolites linked to glutathione, nucleotide, and aspartate-glutamate metabolism, suggesting a higher capacity for redox regulation to tolerate drug-induced oxidative damage. Our findings demonstrate that ozonide resistance can emerge through a novel K13 mutation on the background of existing artemisinin-resistance k13 alleles.

microbiology↗

bioRxiv2025

Comparative metagenomics using pan-metagenomics graphs

Identifying microbial genomic factors underlying human phenotypes is a key goal of microbiome research. Sequence graphs are a highly effective tool for genome comparisons because they enable high-resolution de novo analyses that capture and contextualize complex genomic variation. However, applying sequence graphs to complex microbial communities remains challenging due to the scale and complexity of metagenomic data. Existing multi-sample sequence graphs used in these settings are highly complex, computationally expensive, less accurate than single-sample alternatives, and often involve arbitrary coarse-graining. Here, we present copangraph, a multi-sample sequence-graph-based analysis framework for comprehensive comparisons of genomic variation across metagenomes. Copangraph uses a novel homology-based graph, which provides both non-arbitrary, evolutionary-motivated grouping of sequences into the same node as well as flexibility in the scale of variation represented by the graph. Its construction relies on hybrid coassembly, a new coassembly approach in which single-sample graphs are first constructed separately and are then merged to create a multi-sample graph. We also present an algorithm that uses paired-end reads to improve detection of contiguous genomic regions, increasing accuracy. Our results demonstrate that copangraph captures sequence and variant information more accurately than alternative methods, provides graphs that are more suitable for comparative analysis than de Bruijn graphs, and is computationally tractable. We show that copangraph reflects meaningful metagenomic variation across diverse scenarios. Importantly, it enables significantly better performance than other metagenomic representations when predicting the gut colonization trajectories of Vancomycin-resistant Enterococcus. Our results underscore the value of our multi-sample, graph-based framework for comparative metagenomic analyses.

bioinformatics↗

bioRxiv2025

A generalizable cross-continent prediction of esophageal squamous cell carcinoma using the oral microbiome

Esophageal squamous cell carcinoma (ESCC) is a disease with limited tools for early screening and a poor prognosis. Symptoms typically appear late, and early cancer is hard to detect without endoscopic screening, which is inaccessible in most high-risk areas. Saliva is easily accessible, and its microbiome composition can serve as a marker for upper gastrointestinal tract disease. We studied the potential utility of an oral microbiome signature for ESCC in South Africa, a region with a high incidence of the disease. In a cohort of 48 ESCC patients and 110 controls, we found marked alterations in the oral microbiome in patients with ESCC, including significantly reduced alpha diversity and increased Fusobacterium nucleatum. We devised machine learning models that classify ESCC using microbiome data, finding good performance on held-out samples (area under receiver operating characteristic curve of 0.96), and demonstrated generalization to data across independent studies conducted in different geographic regions (0.64-0.81). Overall, our results demonstrate the potential of the oral microbiome to serve as a non-invasive screening tool for ESCC.

microbiology↗

bioRxiv2025

Shared Binding Site but Divergent Resistance Profiles Uncover Novel Resistance Mechanisms in Plasmodium HSP90 Inhibitors

Drug resistance is a widespread problem across therapeutic areas including malaria, but what accounts for resistance propensity remains poorly understood. Here, we reveal that two HSP90 inhibitors targeting the identical ATP-binding site exhibit dramatically different resistance profiles in P. falciparum. Geldanamycin readily selected 10 distinct resistance mutations conferring up to 22-fold resistance, while AUY-922 required 44 weeks to yield a single A41S mutation with only 2-fold resistance to AUY-922 but not to geldanamycin. Resistance mapping in parasites and yeast revealed geldanamycin resistance mutations distributed throughout the binding pocket whereas AUY-922 resistance mutations localized close to the ATP-binding site. Unexpectedly, the A41S mutation enhanced AUY-922 binding affinity without changing geldanamycin binding. In silico analysis suggested this enhancement occurs through additional hydrogen bonding, yet stronger binding correlated with resistance. In yeast, A41S had opposite effects, hypersensitizing cells to all HSP90 inhibitors tested. Additionally, conditional HSP90 knockdown increased geldanamycin sensitivity but left AUY-922 activity unaffected, indicating different target dependencies despite shared binding sites. Based on these data, we propose a multi-target hypothesis where AUY-922s lower resistance risk stems from engaging multiple HSP90 family members. Our findings reveal how enhanced drug-target binding can paradoxically correlate with resistance and demonstrate that resistance risk cannot be predicted from binding site identity alone, providing insights for developing more durable drugs across therapeutic areas.

microbiology↗

bioRxiv2025

A novel post-translational modification of fimbriae drives pathogenicity in Klebsiella pneumoniae

Multi-drug resistant Gram-negative bacteria, including carbapenem-resistant Klebsiella pneumoniae (CRKp), are a public health emergency. The predominant CRKp sequence type worldwide is ST258. However, the factors underlying ST258s epidemic success are not well defined. The understudied two-component system CrrAB is a genomic feature of ST258 and has been hypothesized to contribute to its global dominance. Despite this, the molecular details underpinning CrrABs contribution to ST258 pathogenicity are not well understood. We used RNA-sequencing to identify the regulon of CrrA and found that CrrAB induces the expression of a novel gene, encoding Crr-regulated fimbriae modifying protein (CfmP). CfmP post-translationally modifies fimbriae to significantly increase host cell adhesion and high bacterial loads within the host, consequently increasing ST258 virulence. CrrAB also drives high antibiotic resistance in CRKp. Thus, our data places CrrAB at the intersection of virulence and antibiotic resistance supporting its function as an important regulatory system driving the pathogenicity of ST258.

microbiology↗

bioRxiv2025

Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles

In microbiome studies, sample processing errors are frequent and difficult to detect, especially in large studies involving multiple sites, personnel, and sample types. We present two complementary approaches to identify such errors using host DNA profiled via metagenomic sequencing of microbiome samples. The first approach compares host SNPs inferred from metagenomics to independently obtained genotypes (e.g., microarray genotypes) to match samples to their donors, while the second method compares metagenomics-inferred SNPs between samples to identify samples supplied by the same donor. Furthermore, we demonstrate that combining these methods with experimental metadata provides greater confidence in the identification of errors. Analyzing a longitudinal vaginal microbiome dataset, we demonstrate the ability of our approach to identify mislabeled samples. Using subsampling, we further show that our methods are robust to low sequencing coverage. Overall, our analysis highlights the frequency of processing errors in microbiome studies. We therefore recommend applying error-detection methods in all studies with suitable data.

bioinformatics↗

bioRxiv2024

Early prediction of preeclampsia using the first trimester vaginal microbiome

Preeclampsia is a severe obstetrical syndrome which contributes to 10-15% of all maternal deaths. Although the mechanisms underlying systemic damage in preeclampsia--such as impaired placentation, endothelial dysfunction, and immune dysregulation--are well studied, the initial triggers of the condition remain largely unknown. Furthermore, although the pathogenesis of preeclampsia begins early in pregnancy, there are no early diagnostics for this life-threatening syndrome, which is typically diagnosed much later, after systemic damage has already manifested. Here, we performed deep metagenomic sequencing and multiplex immunoassays of vaginal samples collected during the first trimester from 124 pregnant individuals, including 62 who developed preeclampsia with severe features. We identified multiple significant associations between vaginal immune factors, microbes, clinical factors, and the early pathogenesis of preeclampsia. These associations vary with BMI, and stratification revealed strong associations between preeclampsia and Bifidobacterium spp., Prevotella timonensis, and Sneathia vaginalis. Finally, we developed machine learning models that predict the development of preeclampsia using this first trimester data, collected ~5.7 months prior to clinical diagnosis, with an auROC of 0.78. We validated our models using data from an independent cohort (MOMS-PI), achieving an auROC of 0.80. Our findings highlight robust associations among the vaginal microbiome, local host immunity, and early pathogenic processes of preeclampsia, paving the way for early detection, prevention and intervention for this devastating condition.

microbiology↗

bioRxiv2024

Identification of the drug/metabolite transporter 1 as a marker of quinine resistance in a NF54xCam3.II P. falciparum genetic cross.

The genetic basis of Plasmodium falciparum resistance to quinine (QN), a drug used to treat severe malaria, has long been enigmatic. To gain further insight, we used FRG-NOD human liver-chimeric mice to conduct a P. falciparum genetic cross between QN-resistant (Cam3.II) and QN-sensitive (NF54) parasites, which also differ in their susceptibility to chloroquine (CQ). By applying different selective conditions to progeny pools prior to cloning, we recovered 120 unique recombinant progeny. Drug profiling and quantitative trait loci analyses of the progeny revealed predominant peaks on chromosomes 7 and 12 associated with CQ and QN resistance, that is consistent with a multifactorial mechanism of resistance for these compounds. CQ and monodesethyl-CQ (md-CQ) resistance mapped to a chromosome 7 region harboring pfcrt as expected. However, for QN, resistance mapped to a dominant chromosome 7 peak centered 295 kb downstream of pfcrt, with pfcrt showing a smaller peak. We identified the drug/metabolite transporter 1 (DMT1) as the top chromosome 7 candidate due to its structural similarity to PfCRT and proximity to the peak. Deleting DMT1 in QN-resistant Cam3.II parasites significantly sensitized the parasite to QN but not to the other drugs tested, suggesting that DMT1 mediates QN response specifically. We localized DMT1 to structures associated with vesicular trafficking, as well as the parasitophorous vacuolar membrane, lipid bodies, and the digestive vacuole. We also observed that mutant DMT1 transports more QN than the wild-type isoform in vitro. Gene editing confirmed an additional role for mutant PfCRT in mediating QN resistance. In addition, we identified an ATP-dependent zinc metalloprotease (FtsH1) as one of the top candidates in the chromosome 12 locus and confirmed its role as a potential mediator of QN resistance and a modulator of md-CQ resistance using CRISPR/Cas9 SNP-edited lines. Interestingly, this chromosome 12 region mapped to resistance to both CQ and QN and was preferentially co-inherited with pfcrt. Our study demonstrates that DMT1 is a novel marker of QN resistance and that a new chromosome 12 locus associates with CQ and QN response, with ftsh1 as a potential candidate, suggesting these genes in addition to pfcrt should be genotyped in surveillance and clinical settings.

genetics↗

bioRxiv2024

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

bioinformatics↗

bioRxiv2023

Mapping the genomic landscape of multidrug resistance in Plasmodium falciparum and its impact on parasite fitness

Drug-resistant Plasmodium falciparum parasites have swept across Southeast Asia and now threaten Africa. By implementing a P. falciparum genetic cross using humanized mice, we report the identification of key determinants of resistance to artemisinin (ART) and piperaquine (PPQ) in the dominant Asian KEL1/PLA1 lineage. We mapped k13 as the central mediator of ART resistance and identified secondary markers. Applying bulk segregant analysis, quantitative trait loci mapping and gene editing, our data reveal an epistatic interaction between mutant PfCRT and multicopy plasmepsins 2/3 in mediating high-grade PPQ resistance. Susceptibility and parasite fitness assays implicate PPQ as a driver of selection for KEL1/PLA1 parasites. Mutant PfCRT enhanced susceptibility to lumefantrine, the first-line partner drug in Africa, highlighting a potential benefit of opposing selective pressures with this drug and PPQ. We also identified that the ABCI3 transporter can operate in concert with PfCRT and plasmepsins 2/3 in mediating multigenic resistance to antimalarial agents.

genomics↗

bioRxiv2022

Generation of a mutator parasite to drive resistome discovery in Plasmodium falciparum

In vitro evolution of drug resistance is a powerful approach for identifying antimalarial targets, however key obstacles to eliciting resistance are the parasite inoculum size and mutation rate. Here we sought to increase parasite genetic diversity to potentiate resistance selections by editing catalytic residues of Plasmodium falciparum DNA polymerase {delta}. Mutation accumulation assays revealed a [~]5-8 fold elevation in the mutation rate, with an increase of 13-28 fold in drug-pressured lines. When challenged with KAE609, high-level resistance was obtained more rapidly and at lower inoculum than wild-type parasites. Selections were also successful with an "irresistible" compound, MMV665794 that failed to yield resistance with other strains. Mutations in a previously uncharacterized gene, PF3D7_1359900, which we term quinoxaline resistance protein (QRP1), were validated as causal for resistance to MMV665794 and an analog, MMV007224. The increased genetic repertoire available to this "mutator" parasite can be leveraged to drive P. falciparum resistome discovery.

microbiology↗

bioRxiv2022

Multiple pathways for SARS-CoV-2 resistance to nirmatrelvir

Nirmatrelvir, an oral antiviral targeting the 3CL protease of SARS-CoV-2, has been demonstrated to be clinically useful in reducing hospitalization or death due to COVID-191,2. However, as SARS-CoV-2 has evolved to become resistant to other therapeutic modalities3-9, there is a concern that the same could occur for nirmatrelvir. Here, we have examined this possibility by in vitro passaging of SARS-CoV-2 in increasing concentrations of nirmatrelvir using two independent approaches, including one on a large scale in 480 wells. Indeed, highly resistant viruses emerged from both, and their sequences revealed a multitude of 3CL protease mutations. In the experiment done at a larger scale with many replicates, 53 independent viral lineages were selected with mutations observed at 23 different residues of the enzyme. Yet, several common mutational pathways to nirmatrelvir resistance were preferred, with a majority of the viruses descending from T21I, P252L, or T304I as precursor mutations. Construction and analysis of 13 recombinant SARS-CoV-2 clones, each containing a unique mutation or a combination of mutations showed that the above precursor mutations only mediated low-level resistance, whereas greater resistance required accumulation of additional mutations. E166V mutation conferred the strongest resistance (~100-fold), but this mutation resulted in a loss of viral replicative fitness that was restored by compensatory changes such as L50F and T21I. Structural explanations are discussed for some of the mutations that are proximal to the drug-binding site, as well as cross-resistance or lack thereof to ensitrelvir, another clinically important 3CL protease inhibitor. Our findings indicate that SARS-CoV-2 resistance to nirmatrelvir does readily arise via multiple pathways in vitro, and the specific mutations observed herein form a strong foundation from which to study the mechanism of resistance in detail and to inform the design of next generation protease inhibitors.

microbiology↗

bioRxiv2021

Molecular Pathophysiology of Cardiac Injury and Cardiac Microthrombi in Fatal COVID-19: Insights from Clinico-histopathologic and Single Nuclei RNA Sequencing Analyses

Cardiac injury is associated with critical COVID-19, yet its etiology remains debated. To elucidate the pathogenic mechanisms of COVID-19-associated cardiac injury, we conducted a single-center prospective cohort study of 69 COVID-19 decedents. Of six cardiac histopathologic features, microthrombi was the most commonly detected (n=48, 70%). We tested associations of cardiac microthrombi with biomarkers of inflammation, cardiac injury, and fibrinolysis and with in-hospital antiplatelet therapy, therapeutic anticoagulation, and corticosteroid treatment, while adjusting for multiple clinical factors, including COVID-19 therapies. Higher peak ESR and CRP during hospitalization were independently associated with higher odds of microthrombi. Using single nuclei RNA-sequence analysis, we discovered an enrichment of pro-thrombotic/anti-fibrinolytic, extracellular matrix remodeling, and immune-potentiating signaling amongst cardiac fibroblasts in microthrombi-positive COVID-19 hearts relative to microthrombi-negative COVID-19. Non-COVID-19 non-failing hearts were used as reference controls. Our cumulative findings identify the specific transcriptomic changes in cardiac fibroblasts as salient features of COVID-19-associated cardiac microthrombi.

pathology↗

bioRxiv2020

Alteration of menaquinone isoprenoid chain length and antibiotic sensitivity by single amino acid substitution in HepT

ObjectivesStaphylococcus aureus Smith strain is a historical strain widely used for research purposes in animal infection models for testing the therapeutic activity of antimicrobial agents. We found that it displayed higher sensitivity towards lysocin E, a menaquinone (MK) targeting antibiotic, compared to other S. aureus strains. Therefore, we further explored the mechanism of this hypersensitivity. MethodsMK production was analyzed by high-performance liquid chromatography and mass spectrometric analysis. S. aureus Smith genome sequence was completed using a hybrid assembly approach, and the MK biosynthetic genes were compared with other S. aureus strains. The hepT gene was cloned and introduced into S. aureus RN4220 strain using phage mediated recombination, and lysocin E sensitivity was analyzed by the measurement of minimum inhibitory concentration and colony-forming units. ResultsWe found that Smith strain produced MKs with the length of the side chain ranging between 8 - 10, as opposed to other S. aureus strains that produce MKs 7 - 9. We revealed that Smith strain possessed the classical pathway for MK biosynthesis like the other S. aureus. HepT, a polyprenyl diphosphate synthase involved in chain elongation of isoprenoid, in Smith strain was unique with a Q25P substitution. Introduction of hepT from Smith to RN4220 led to the production of MK-10 and an increased sensitivity towards lysocin E. ConclusionsWe found that HepT was responsible for the definition of isoprenoid chain length of MKs and antibiotic sensitivity.

microbiology↗

bioRxiv2019

The antimalarial natural product salinipostin A identifies essential α/β serine hydrolases involved in lipid metabolism in P. falciparum parasites

Salinipostin A (Sal A) is a potent antimalarial marine natural product with an undefined mechanism of action. Using a Sal A-derived activity-based probe, we identify its targets in the Plasmodium falciparum parasite. All of the identified proteins contain /{beta} serine hydrolase domains, and several are essential for parasite growth. One of the essential targets displays high homology to human monoacylglycerol lipase (MAGL) and is able to process lipid esters including a MAGL acylglyceride substrate. This Sal A target is inhibited by the anti-obesity drug Orlistat, which disrupts lipid metabolism and produces disorganized and stalled schizonts similar to Sal A. Resistance selections yielded parasites that showed only minor reductions in sensitivity and that acquired mutations in a protein linked to drug resistance in Toxoplasma gondii. This inability to evolve efficient resistance mechanisms combined with the non-essentiality of human homologs makes the serine hydrolases identified here promising antimalarial targets.

cell biology↗

bioRxiv2019

Epidemiology of Staphylococcus aureus in Neonates on Admission to a Chinese Neonatal Intensive Care Unit

PurposeLittle is known about the molecular epidemiology of Staphylococcus aureus in Chinese neonatal intensive care units (NICUs). We describe the molecular epidemiology of S. aureus isolated from neonates on admission to Beijing Childrens Hospital. MethodsFrom May 2015-March 2016, nasal swabs were obtained on admission from 536 neonates. Cultures were also obtained from body sites with suspected infections. S. aureus isolates were characterized by staphylococcal chromosomal cassette (SCCmec) type, staphylococcal protein A (spa) type, multilocus sequence type (MLST), sasX gene, antimicrobial susceptibility and cytotoxicity. Logistic regression assessed risk factors for colonization. ResultsOverall, 92 (18%) infants were colonized with S. aureus and 23 (4%) were diagnosed with culture-positive S. aureus infection. Of the colonized infants, 72% harbored MSSA, while 74% of infected infants were culture-positive for MRSA. Risk factors for colonization included female sex, age 7-28 days, birthweight and vaginal delivery. The most common MRSA and MSSA clones were community-associated ST59-SCCmecIVa-t437 (60%) and ST188-t189 (15%), respectively. The sasX gene was not detected. Some MSSA isolates (16%) were penicillin-susceptible and some MRSA isolates (18%) were oxacillin-susceptible. MRSA and MSSA had similar cytotoxicity, but colonizing strains were less cytotoxic than strains associated with infections. ConclusionsS. aureus colonization was common in infants admitted to our NICU and two community-associated clones predominated. Several non-modifiable risk factors for S. aureus colonization were identified. These results suggest that screening infants for S. aureus upon admission and targeting decolonization of high-risk infants and/or those colonized with high-risk clones could be useful to prevent transmission.

microbiology↗

bioRxiv2018

Mechanism and resistance for antimycobacterial activity of a fluoroquinophenoxazine compound

We have previously reported the inhibition of bacterial topoisomerase I activity by a fluoroquinophenoxazine compound (FP-11g) with a 6-bipiperidinyl lipophilic side chain that exhibited promising antituberculosis activity (MIC = 2.5 M against Mycobacterium tuberculosis, SI = 9.8). Here, we found that the compound is bactericidal towards Mycobacterium smegmatis, resulting in greater than 5 Log10 reduction in colony-forming units [cfu]/mL following a 10 h incubation at 1.25 M (4X MIC) concentration. Growth inhibition (MIC = 50 M) and reduction in cfu could also be observed against a clinical isolate of Mycobacterium abscessus. Stepwise isolation of resistant mutants of M. smegmatis was conducted to explore the mechanism of resistance. Mutations in the resistant isolates were identified by direct comparison of whole-genome sequencing data from mutant and wild-type isolates. These include mutations in genes likely to affect the entry and retention of the compound. FP-11g inhibits Mtb topoisomerase I and Mtb gyrase with IC50 of 0.24 and 31.5 M, respectively. Biophysical analysis showed that FP-11g binds DNA as an intercalator but the IC50 for inhibition of Mtb topoisomerase I activity is >10 fold lower than the compound concentrations required for producing negatively supercoiled DNA during ligation of nicked circular DNA. Thus, the DNA-binding property of FP-11g may contribute to its antimycobacterial mechanism, but that alone cannot account for the observed inhibition of Mtb topoisomerase I.

microbiology↗