Evolution of carbapenem resistance in Acinetobacter baumannii during a prolonged infection

Prevalence and characteristics of tigecycline- and carbapenem-resistant adeN-truncated Acinetobacter baumannii: a genomic epidemiological analysis

adeN-truncated Acinetobacter baumannii (ATAB) isolates are associated with elevated tigecycline resistance and enhanced virulence, yet its epidemic dynamics and genomic features remain poorly understood. This study aimed to investigate the epidemiology of ATAB isolates, identify infection risk factors, and assess their impact on patient prognosis. The prevalence of ATAB isolates in a tertiary care teaching hospital (Wenzhou, China) from January 2018 to December 2022 was determined via polymerase chain reaction (PCR) screening. Whole-genome sequencing and genomic analysis were conducted to explore the epidemiology and genomic characteristics of 254 ATAB isolates. Clinical data analysis was performed to identify risk factors for ATAB infection and its correlation with patient prognosis. The results of local sample analysis showed that adeN truncation was identified in 26.5% (486/1834) of the patient isolates, with the monthly prevalence peaking at 64.9% (24/37). The capsular types of ATAB isolates were primarily KL2, whereas adeN-complete isolates exhibited a greater capsular diversity. ATAB could evolve within the hospital and lead to multiple nosocomial clonal transmissions. Most ATAB isolates exhibited co-resistance to carbapenems and tigecycline. ICU admission and use of immunosuppressants were significant risk factors for ATAB isolate infection. Patients infected with ATAB isolates had significantly higher 28-day all-cause mortality (32.8%, 20/61) compared to those infected with adeN-complete isolates (11.5%, 7/61, P < 0.01). Bioinformatics analysis of the 18,946 completed and draft A. baumannii genome assemblies from the GenBank database showed that ATAB isolates were widely prevalent worldwide. This study highlights the importance of early identification and monitoring of ATAB isolates as a critical marker for hospital infection control.

Emergence and global spread of a dominant multidrug-resistant clade within Acinetobacter baumannii

The proliferation of multi-drug resistant (MDR) bacteria is driven by the global spread of epidemic lineages that accumulate antimicrobial resistance genes (ARGs). Acinetobacter baumannii, a leading cause of nosocomial infections, displays resistance to most frontline antimicrobials and represents a significant challenge to public health. In this study, we conduct a comprehensive genomic analysis of over 15,000 A. baumannii genomes to identify a predominant epidemic super-lineage (ESL) accounting for approximately 70% of global isolates. Through hierarchical classification of the ESL into distinct lineages, clusters, and clades, we identified a stepwise evolutionary trajectory responsible for the worldwide expansion and transmission of A. baumannii over the last eight decades. We observed the rise and global spread of a previously unrecognized Clade 2.5.6, which emerged in East Asia in 2006. The epidemic of the clade is linked to the ongoing acquisition of ARGs and virulence factors facilitated by genetic recombination. Our results highlight the necessity for One Health-oriented research and interventions to address the spread of this MDR pathogen.

Phenotypic and genetic heterogeneity of Acinetobacter baumannii in the course of an animal chronic infection

Acinetobacter baumannii is a nosocomial pathogen associated with various infections, including urinary tract infections (UTIs). In the course of an infection, A. baumannii is known to rapidly become resistant to antibiotic therapy, but much less is known about possible adaptation without antibiotic pressure. Through a retrospective study, we investigated within-host genetic diversity during a subclinical 5-year UTI in an animal-patient after withdrawal of colistin treatment. We conducted whole-genome sequencing and phenotypic assays on 17 clonally related isolates from the Sequence Type 25 lineage. Phylogenomic analysis revealed their proximity with animal and human strains from the same country suggesting zoonotic transmission (France). In this case study, the clonally related strains presented variations in genome sizes and nucleotide sequences. Over the course of the infection, A. baumannii underwent genome reduction through insertion sequence (IS) recombination, phage excision or plasmid curing. Alongside this global genome reduction, we observed an expansion of IS17, initially located on the endogenous large plasmid. Genetic variations were mainly located in biofilm formation and metabolism genes. We observed repeated variations affecting three biofilm genes and two adhesion operons associated with weak biofilm-forming capacity. Conversely, only two metabolic genes were recurrently affected, and phenotypic assays indicated a rather stable metabolism profile between the isolates suggesting minor adaptations to its host. Lastly, an overall decreased antibiotic resistance - expected in the absence of antibiotic treatment - contrasted with a conserved colistin resistance due to a pmrB mutation among the isolates.

A review of the fighting Acinetobacter baumannii on three fronts: antibiotics, phages, and nanoparticles

In the current era of antibiotic resistance, researchers are exploring alternative ways to treat bacterial infections that are resistant to multiple drugs. Acinetobacter baumannii (A. baumannii) is a bacterium that is commonly encountered in clinical settings and is known to be resistant to several drugs. Due to the increase in drug-resistant infections caused by this bacteria, there is an urgent need to investigate alternative treatment options such as phage therapy and combination therapy. Despite the success of phages in some cases, there are some limitations in their clinical application that can be overcome by combining phages with other substrates such as nanoparticles to improve their function. The integration of nanotechnology with phage therapy against A. baumannii promises to overcome antibiotic resistance. By exploiting the targeted delivery and controlled release capabilities of nanoparticles, we can enhance the therapeutic potential of phages while minimizing their limitations. Continued research in this field will undoubtedly pave the way for more effective and precise treatments against A. baumannii infections and provide hope in the fight against antibiotic-resistant bacteria.

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

Genomics unveils country-to-country transmission between animal hospitals of a multidrug-resistant and sequence type 2 Acinetobacter baumannii clone

Acinetobacter baumannii is a globally distributed opportunistic pathogen in human health settings, including in intensive care units (ICUs). We investigated the contamination of a French small animal ICU with A. baumannii. We discovered repeated animal contamination by A. baumannii, and phylogenetic analysis traced contamination back to a potential foreign animal origin. Genomic analysis combined with antibiotic susceptibility testing revealed heteroresistance to penicillin and aminoglycoside mediated by insertion sequence dynamics and also suggest a potential cross-resistance to human-restricted piperacillin-tazobactam combination. The A. baumannii isolates of the animal ICU belong to the International Clone 2 commonly found in human health settings. Our results suggest a high adaptation of this lineage to healthcare settings and provide questions on the requirements for genetic determinants enabling adaptation to host and abiotic conditions.

Structural and functional diversity of Resistance-Nodulation-Division (RND) efflux pump transporters with implications for antimicrobial resistance

SUMMARYThe discovery of bacterial efflux pumps significantly advanced our understanding of how bacteria can resist cytotoxic compounds that they encounter. Within the structurally and functionally distinct families of efflux pumps, those of the Resistance-Nodulation-Division (RND) superfamily are noteworthy for their ability to reduce the intracellular concentration of structurally diverse antimicrobials. RND systems are possessed by many Gram-negative bacteria, including those causing serious human disease, and frequently contribute to resistance to multiple antibiotics. Herein, we review the current literature on the structure-function relationships of representative transporter proteins of tripartite RND efflux pumps of clinically important pathogens. We emphasize their contribution to bacterial resistance to clinically used antibiotics, host defense antimicrobials and other biocides, as well as highlighting structural similarities and differences among efflux transporters that help bacteria survive in the face of antimicrobials. Furthermore, we discuss technical advances that have facilitated and advanced efflux pump research and suggest future areas of investigation that will advance antimicrobial development efforts.

Engineering G protein-coupled receptors for stabilization

G protein-coupled receptors (GPCRs) are one of the most important families of targets for drug discovery. One of the limiting steps in the study of GPCRs has been their stability, with significant and time-consuming protein engineering often used to stabilize GPCRs for structural characterization and drug screening. Unfortunately, computational methods developed using globular soluble proteins have translated poorly to the rational engineering of GPCRs. To fill this gap, we propose GPCR-tm, a novel and personalized structurally driven web-based machine learning tool to study the impacts of mutations on GPCR stability. We show that GPCR-tm performs as well as or better than alternative methods, and that it can accurately rank the stability changes of a wide range of mutations occurring in various types of class A GPCRs. GPCR-tm achieved Pearson's correlation coefficients of 0.74 and 0.46 on 10-fold cross-validation and blind test sets, respectively. We observed that the (structural) graph-based signatures were the most important set of features for predicting destabilizing mutations, which points out that these signatures properly describe the changes in the environment where the mutations occur. More specifically, GPCR-tm was able to accurately rank mutations based on their effect on protein stability, guiding their rational stabilization. GPCR-tm is available through a user-friendly web server at https://biosig.lab.uq.edu.au/gpcr_tm/.

AI-Driven Enhancements in Drug Screening and Optimization

The greatest challenge in drug discovery remains the high rate of attrition across the different phases of the process, which cost the industry billions of dollars every year. While all phases remain crucial to ensure pharmaceutical-level safety, quality, and efficacy of the end product, streamlining these efforts toward compounds with success potential is pivotal for a more efficient and cost-effective process. The use of artificial intelligence (AI) within the pharmaceutical industry aims at just this, and has applications in preclinical screening for biological activity, optimization of pharmacokinetic properties for improved drug formulation, early toxicity prediction which reduces attrition, and pre-emptively screening for genetic changes in the biological target to improve therapeutic longevity. Here, we present a series of in silico tools that address these applications in small molecule development and describe how they can be embedded within the current pharmaceutical development pipeline.

The whole-genome molecular epidemiology of sequential isolates of Acinetobacter baumannii colonizing the rectum of patients in an adult intensive care unit of a tertiary hospital

IMPORTANCE

Acinetobacter baumannii is a multidrug-resistant nosocomial pathogen that colonizes and infects debilitated patients in the ICU. There is very little information on the genomic characteristics of colonizing strains. This information is important to understand the evolution of lineages of A. baumannii that develop resistance while patients receive antibiotic treatment in the ICU. Our study demonstrated different patterns of colonization of the rectum of ICU patients with different STs of A. baumannii while one ST colonized all patients. Some STs carried more antibiotic resistance genes compared to others. However, there was a correlation between ST and a particular resistance gene profile. Our results further elucidate the dynamics of enteric colonization of this opportunistic pathogen.

Comparative genotypic characterization related to antibiotic resistance phenotypes of clinical carbapenem-resistant Acinetobacter baumannii MTC1106 (ST2) and MTC0619 (ST25)

BACKGROUND

The prevalence of Acinetobacter baumannii in nosocomial infections and its remarkable ability to develop antimicrobial resistance have been a critical issue in hospital settings. Here, we examined the genomic features related to resistance phenotype displayed by carbapenem-resistant A. baumannii (CRAB) MTC1106 (ST2) and MTC0619 (ST25).

RESULTS

Resistome analysis of both strains revealed that MTC1106 possessed higher numbers of antimicrobial resistance genes compared to MTC0619. Some of those genetic determinants were present in accordance with the susceptibility profile of the isolates. The predicted ISAba1 region upstream of blaOXA-23 gene was related to carbapenem resistance since this IS element was well-characterized to mediate overexpression of carbapenemase genes and eventually provided capability to confer resistance. Unlike MTC0619 strain, which only carried class B and D β-lactamase genes, MTC1106 strain also possessed blaTEM-1D, a class A β-lactamase. Regarding to aminoglycosides resistance, MTC0619 contained 5 related genes in which all of them belonged to three groups of aminoglycosides modifying enzyme (AME), namely, N-acetyltransferase (AAC), O-nucleotidyltransferase (ANT), and O-phosphotransferase (APH). On the other hand, MTC1106 lacked only the AAC of which found in MTC0619, yet it also carried an armA gene encoding for 16S rRNA methyltransferase. Two macrolides resistance genes, mph(E) and msr(E), were identified next to the armA gene of MTC1106 isolate in which they encoded for macrolide 2'-phosphotransferase and ABC-type efflux pump, respectively. Besides acquired resistance genes, some chromosomal genes and SNPs associated with resistance to fluoroquinolones (i.e. gyrA and parC) and colistin (i.e. pmrCAB, eptA, and emrAB) were observed. However, gene expression analysis suggested that the genetic determinants significantly contributing to low-level colistin resistance remained unclear. In addition, similar number of efflux pumps genes were identified in both lineages with only the absence of adeC, a part of adeABC RND-type multidrug efflux pump in MTC0619 strain.

CONCLUSIONS

We found that MTC1106 strain harbored more antimicrobial resistance genes and showed higher resistance to antibiotics than MTC0619 strain. Regarding genomic characterization, this study was likely the first genome comparative analysis of CARB that specifically included isolates belonging to ST2 and ST25 which were widely spread in Thailand. Taken altogether, this study suggests the importance to monitor the resistance status of circulating A. baumannii clones and identify genes that may contribute to shifting the resistance trend among isolates.

Outer Membrane Proteins and Efflux Pumps Mediated Multi-Drug Resistance in Salmonella: Rising Threat to Antimicrobial Therapy

Despite colossal achievements in antibiotic therapy in recent decades, drug-resistant pathogens have remained a leading cause of death and economic loss globally. One such WHO-critical group pathogen is Salmonella. The extensive and inappropriate treatments for Salmonella infections have led from multi-drug resistance (MDR) to extensive drug resistance (XDR). The synergy between efflux-mediated systems and outer membrane proteins (OMPs) may favor MDR in Salmonella. Differential expression of the efflux system and OMPs (influx) and positional mutations are the factors that can be correlated to the development of drug resistance. Insights into the mechanism of influx and efflux of antibiotics can aid in developing a structurally stable molecule that can be proficient at escaping from the resistance loops in Salmonella. Understanding the strategic responsibilities and developing policies to address the surge of drug resistance at the national, regional, and global levels are the needs of the hour. In this Review, we attempt to aggregate all the available research findings and delineate the resistance mechanisms by dissecting the involvement of OMPs and efflux systems. Integrating major OMPs and the efflux system's differential expression and positional mutation in Salmonella may provide insight into developing strategic therapies for one health application.

Global genomic epidemiology of chromosomally mediated non-enzymatic carbapenem resistance in Acinetobacter baumannii: on the way to predict and modify resistance

Introduction

Although carbapenemases are frequently reported in resistant A. baumannii clinical isolates, other chromosomally mediated elements of resistance that are considered essential are frequently underestimated. Having a wide substrate range, multidrug efflux pumps frequently underlie antibiotic treatment failure. Recognizing and exploiting variations in multidrug efflux pumps and penicillin-binding proteins (PBPs) is an essential approach in new antibiotic drug discovery and engineering to meet the growing challenge of multidrug-resistant Gram-negative bacteria.

Methods

A total of 980 whole genome sequences of A. baumannii were analyzed. Nucleotide sequences for the genes studied were queried against a custom database of FASTA sequences using the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) system. The correlation between different variants and carbapenem Minimum Inhibitory Concentrations (MICs) was studied. PROVEAN and I-Mutant predictor suites were used to predict the effect of the studied amino acid substitutions on protein function and protein stability. Both PsiPred and FUpred were used for domain and secondary structure prediction. Phylogenetic reconstruction was performed using SANS serif and then visualized using iTOL and Phandango.

Results

Exhibiting the highest detection rate, AdeB codes for an important efflux-pump structural protein. T48V, T584I, and P660Q were important variants identified in the AdeB-predicted multidrug efflux transporter pore domains. These can act as probable targets for designing new efflux-pump inhibitors. Each of AdeC Q239L and AdeS D167N can also act as probable targets for restoring carbapenem susceptibility. Membrane proteins appear to have lower predictive potential than efflux pump-related changes. OprB and OprD changes show a greater effect than OmpA, OmpW, Omp33, and CarO changes on carbapenem susceptibility. Functional and statistical evidence make the variants T636A and S382N at PBP1a good markers for imipenem susceptibility and potential important drug targets that can modify imipenem resistance. In addition, PBP3_370, PBP1a_T636A, and PBP1a_S382N may act as potential drug targets that can be exploited to counteract imipenem resistance.

Conclusion

The study presents a comprehensive epidemiologic and statistical analysis of potential membrane proteins and efflux-pump variants related to carbapenem susceptibility in A. baumannii, shedding light on their clinical utility as diagnostic markers and treatment modification targets for more focused studies of candidate elements.

Acinetobacter baumannii GC2 Sublineage Carrying the aac(6')-Im Amikacin, Netilmicin, and Tobramycin Resistance Gene Cassette

The aminoglycoside antibiotics amikacin, gentamicin, and tobramycin are important therapeutic options for Acinetobacter iinfections. Several genes that confer resistance to one or more of these antibiotics are prevalent in the globally distributed resistant clones of Acinetobacter baumannii, but the aac(6')-Im (aacA16) gene (amikacin, netilmicin, and tobramycin resistance), first reported in isolates from South Korea, has rarely been reported since. In this study, GC2 isolates (1999 to 2002) from Brisbane, Australia, carrying aac(6')-Im and belonging to the ST2:ST423:KL6:OCL1 type were identified and sequenced. The aac(6')-Im gene and surrounds have been incorporated into one end of the IS26-bounded AbGRI2 antibiotic resistance island and are accompanied by a characteristic 70.3-kbp deletion of adjacent chromosome. The compete genome of the 1999 isolate F46 (RBH46) includes only two copies of ISAba1 (in AbGRI1-3 and upstream of ampC) but later isolates, which differ from one another by <10 single nucleotide differences (SND), carry two to seven additional shared copies. Several complete GC2 genomes with aac(6')-Im in an AbGRI2 island (2004 to 2017; several countries) found in GenBank and two additional Australian A. baumannii isolates (2006) carry different gene sets, KL2, KL9, KL40, or KL52, at the capsule locus. These genomes include ISAba1 copies in a different set of shared locations. The distribution of SND between F46 and AYP-A2, a 2013 ST2:ST208:KL2:OCL1 isolate from Victoria, Australia, revealed that a 640-kbp segment that includes KL2 and the AbGRI1 resistance island replaces the corresponding region in F46. Over 1,000 A. baumannii draft genomes also include aac(6')-Im, indicating that it is currently globally disseminated and significantly underreported. IMPORTANCE Aminoglycosides are important therapeutic options for treatment of Acinetobacter infections. Here, we show that a little-known aminoglycoside resistance gene, aac(6')-Im (aacA16), that confers amikacin, netilmicin, and tobramycin resistance has been circulating undetected for many years in a sublineage of A. baumannii global clone 2 (GC2), generally with a second aminoglycoside resistance gene, aacC1, which confers resistance to gentamicin. These two genes are commonly found together in GC2 complete and draft genomes and globally distributed. One isolate appears to be ancestral, as its genome contains few ISAba1 copies, providing insight into the original source of this insertion sequence (IS), which is abundant in most GC2 isolates. Tracking ISAba1 spread can provide a simple means to track the development and ongoing evolution as well as the dissemination of specific lineages and detect the formation of many sublineages. The complete ancestral genome will provide an essential base point for tracking this process.

Using Graph-Based Signatures to Guide Rational Antibody Engineering

Antibodies are essential experimental and diagnostic tools and as biotherapeutics have significantly advanced our ability to treat a range of diseases. With recent innovations in computational tools to guide protein engineering, we can now rationally design better antibodies with improved efficacy, stability, and pharmacokinetics. Here, we describe the use of the mCSM web-based in silico suite, which uses graph-based signatures to rapidly identify the structural and functional consequences of mutations, to guide rational antibody engineering to improve stability, affinity, and specificity.

Nanopore Electrochemistry for Pathogen Detection

Pathogen infections have seriously threatened human health, and there is an urgent demand for rapid and efficient pathogen identification to provide instructions in clinical diagnosis and therapeutic intervention. Recently, nanopore technology, a rapidly maturing technology which delivers ultrasensitive sensing and high throughput in real-time and at low cost, has achieved success in pathogen detection. Furthermore, the remarkable development of nanopore sequencing, for example, the MinION sequencer from Oxford Nanopore Technologies (ONT) as a competitive sequencing technology, has facilitated the rapid analysis of disease-related microbiomes at the whole-genome level and on a large scale. Here, we highlighted recent advances in nanopore approaches for pathogen detection at the single-molecule level. We also overviewed the applications of nanopore sequencing in pathogenic bacteria identification and diagnosis. In the end, we discussed the challenges and future developments of nanopore technology as promising tools for the management of infections, which may be helpful to aid understanding as well as decision-making.

Phage-antibiotic combination is a superior treatment against Acinetobacter baumannii in a preclinical study

BACKGROUND

Clinical phage therapy is often delivered alongside antibiotics. However, the phenomenon of phage-antibiotic synergy has been mostly studied in vitro. Here, we assessed the in vivo bactericidal effect of a phage-antibiotic combination on Acinetobacter baumannii AB900 using phage øFG02, which binds to capsular polysaccharides and leads to antimicrobial resensitisation in vitro.

METHODS

We performed a two-stage preclinical study using a murine model of severe A. baumannii AB900 bacteraemia. In the first stage, with an endpoint of 11 h, mice (n = 4 per group) were treated with either PBS, ceftazidime, phage øFG02, or the combination of phage and ceftazidime. The second stage involved only the latter two groups (n = 5 per group), with a prolonged endpoint of 16 h. The primary outcome was the average bacterial burden from four body sites (blood, liver, kidney, and spleen). Bacterial colonies from phage-treated mice were retrieved and screened for phage-resistance.

FINDINGS

In the first stage, the bacterial burden (CFU/g of tissue) of the combination group (median: 4.55 × 10⁵; interquartile range [IQR]: 2.79 × 10⁵-2.81 × 10⁶) was significantly lower than the PBS (median: 2.42 × 10⁹; IQR: 1.97 × 10⁹-3.48 × 10⁹) and ceftazidime groups (median: 3.86 × 10⁸; IQR: 2.15 × 10⁸-6.35 × 10⁸), but not the phage-only group (median: 1.28 × 10⁷; IQR: 4.71 × 10⁶-7.13 × 10⁷). In the second stage, the combination treatment (median: 1.72 × 10⁶; IQR: 5.11 × 10⁵-4.00 × 10⁶) outperformed the phage-only treatment (median: 7.46 × 10⁷; IQR: 1.43 × 10⁷-1.57 × 10⁸). Phage-resistance emerged in 96% of animals receiving phages, and all the tested isolates (n = 11) had loss-of-function mutations in genes involved in capsule biosynthesis and increased sensitivity to ceftazidime.

INTERPRETATION

øFG02 reliably drives the in vivo evolution of A. baumannii AB900 towards a capsule-deficient, phage-resistant phenotype that is resensitised to ceftazidime. This mechanism highlights the clinical potential of using phage therapy to target A. baumannii and restore antibiotic activity.

FUNDING

National Health and Medical Research Council (Australia).

Synergistic Inhibitory Effect of Polymyxin B in Combination with Ceftazidime against Robust Biofilm Formed by Acinetobacter baumannii with Genetic Deficiency in AbaI/AbaR Quorum Sensing

Carbapenem resistance of Acinetobacter baumannii poses challenges to public health. Biofilm contributes to the persistence of A. baumannii cells. This study was designed to investigate the genetic relationships among carbapenem resistance, polymyxin resistance, multidrug resistance, biofilm formation, and surface-associated motility and evaluate the antibiofilm effect of polymyxin in combination with other antibiotics. A total of 103 clinical A. baumannii strains were used to determine antibiotic susceptibility, biofilm formation capacity, and motility. Enterobacterial repetitive intergenic consensus (ERIC)-PCR fingerprinting was used to determine the genetic variation among strains. The distribution of 17 genes related to the resistance-nodulation-cell division (RND)-type efflux, autoinducer-receptor (AbaI/AbaR) quorum sensing, oxacillinases (OXA)-23, and insertion sequence of ISAba1 element was investigated. The representative strains were chosen to evaluate the gene transcription and the antibiofilm activity by polymyxin B (PB) in combination with merapenem, levofloxacin, and ceftazidime, respectively. ERIC-PCR-dependent fingerprints were found to be associated with carbapenem resistance and multidrug resistance. The presence of bla_OXA-23 was found to correlate with genes involved in ISAba1 insertion, AbaI/AbaR quorum sensing, and AdeABC efflux. Carbapenem resistance was observed to be negatively correlated with biofilm formation and positively correlated with motility. PB in combination with ceftazidime displayed a synergistic antibiofilm effect against robust biofilm formed by an A. baumannii strain with deficiency in AbaI/AbaR quorum sensing. Our results not only clarify the genetic correlation among carbapenem resistance, biofilm formation, and pathogenicity in a certain level but also provide a theoretical basis for clinical applications of polymyxin-based combination of antibiotics in antibiofilm therapy. IMPORTANCE Deeper explorations of molecular correlation among antibiotic resistance, biofilm formation, and pathogenicity could provide novel insights that would facilitate the development of therapeutics and prevention against A. baumannii biofilm-related infections. The major finding that polymyxin B in combination with ceftazidime displayed a synergistic antibiofilm effect against robust biofilm formed by an A. baumannii strain with genetic deficiency in AbaI/AbaR quorum sensing further provides a theoretical basis for clinical applications of antibiotics in combination with quorum quenching in antibiofilm therapy.

The Impact of Omega-3 Fatty Acids on the Evolution of Acinetobacter baumannii Drug Resistance

The bacterial pathogen Acinetobacter baumannii has emerged as an urgent threat to health care systems. The prevalence of multidrug resistance in this critical human pathogen is closely associated with difficulties in its eradication from the hospital environment and its recalcitrance to treatment during infection. The development of resistance in A. baumannii is in part due to substantial plasticity of its genome, facilitating spontaneous genomic evolution. Many studies have investigated selective pressures imposed by antibiotics on genomic evolution, but the influence of high-abundance bioactive molecules at the host-pathogen interface on mutation and rates of evolution is poorly understood. Here, we studied the roles of host fatty acids in the gain in resistance to common antibiotics. We defined the impact of the polyunsaturated fatty acids arachidonic acid and docosahexaenoic acid on the development of resistance to erythromycin in A. baumannii strain AB5075_UW using a microevolutionary approach. We employed whole-genome sequencing and various phenotypic analyses to characterize microbe-lipid-antibiotic interactions. Cells exposed to erythromycin in the presence of the fatty acids displayed significantly lower rates of development of resistance to erythromycin and, importantly, tetracycline. Subsequent analyses defined diverse means by which host fatty acids influence the mutation rates. This work has highlighted the critical need to consider the roles of host fatty acids in A. baumannii physiology and antimicrobial resistance. Collectively, we have identified a novel means to curb the development of resistance in this critical human pathogen. IMPORTANCE The global distribution of multidrug resistance in A. baumannii has necessitated seeking not only alternative therapeutic approaches but also the means to limit the development of resistance in clinical settings. Highly abundant host bioactive compounds, such as polyunsaturated fatty acids, are readily acquired by A. baumannii during infection and have been illustrated to impact the bacterium's membrane composition and antibiotic resistance. In this work, we show that in vitro supplementation with host polyunsaturated fatty acids reduces the rate at which A. baumannii gains resistance to erythromycin and tetracycline. Furthermore, we discover that the impact on resistance development is closely associated with the primary antimicrobial efflux systems of A. baumannii, which represent one of the major drivers of clinical resistance. Overall, this study emphasizes the potential of host macromolecules in novel approaches to circumvent the difficulties of multidrug resistance during A. baumannii treatment, with fatty acid supplements such as fish oil providing safe and cost-effective ways to enhance host tolerance to bacterial infections.

Whole-Genome Assessment of Clinical Acinetobacter baumannii Isolates Uncovers Potentially Novel Factors Influencing Carbapenem Resistance

Carbapenems-one of the important last-line antibiotics for the treatment of gram-negative infections-are becoming ineffective for treating Acinetobacter baumannii infections. Studies have identified multiple genes (and mechanisms) responsible for carbapenem resistance. In some A. baumannii strains, the presence/absence of putative resistance genes is not consistent with their resistance phenotype-indicating the genomic factors underlying carbapenem resistance in A. baumannii are not fully understood. Here, we describe a large-scale whole-genome genotype-phenotype association study with 349 A. baumannii isolates that extends beyond the presence/absence of individual antimicrobial resistance genes and includes the genomic positions and pairwise interactions of genes. Ten known resistance genes exhibited statistically significant associations with resistance to imipenem, a type of carbapenem: blaOXA-23, qacEdelta1, sul1, mphE, msrE, ant(3")-II, aacC1, yafP, aphA6, and xerD. A review of the strains without any of these 10 genes uncovered a clade of isolates with diverse imipenem resistance phenotypes. Finer resolution evaluation of this clade revealed the presence of a 38.6 kbp conserved chromosomal region found exclusively in imipenem-susceptible isolates. This region appears to host several HTH-type DNA binding transcriptional regulators and transporter genes. Imipenem-susceptible isolates from this clade also carried two mutually exclusive plasmids that contain genes previously known to be specific to imipenem-susceptible isolates. Our analysis demonstrates the utility of using whole genomes for genotype-phenotype correlations in the context of antibiotic resistance and provides several new hypotheses for future research.

Whole-Genome Sequencing Elucidates the Epidemiology of Multidrug-Resistant Acinetobacter baumannii in an Intensive Care Unit

The nosocomial pathogen Acinetobacter baumannii is a frequent cause of healthcare-acquired infections, particularly in critically ill patients, and is of serious concern due to its potential for acquired multidrug resistance. Whole-genome sequencing (WGS) is increasingly used to obtain a high-resolution view of relationships between isolates, which helps in controlling healthcare-acquired infections. Here, we conducted a retrospective study to identify epidemic situations and assess the percentage of transmission in intensive care units (ICUs). Multidrug-resistant A. baumannii (MDR-AB) were continuously isolated from the lower respiratory tract of different patients (at the first isolation in our ICU). We performed WGS, pulsed-field gel electrophoresis (PFGE), and multilocus-sequence typing (MLST) analyses to elucidate bacterial relatedness and to compare the performance of conventional methods with WGS for typing MDR-AB. From June 2017 to August 2018, A. baumannii complex strains were detected in 124 of 796 patients during their ICU stays, 103 of which were MDR-AB. Then we subjected 70 available MDR-AB strains to typing with WGS, PFGE, and MLST. Among the 70 A. baumannii isolates, 38 (54.29%) were isolated at admission, and 32(45.71%) were acquisition isolates. MLST identified 12 unique sequence types, a novel ST (ST2367) was founded. PFGE revealed 16 different pulsotypes. Finally, 38 genotypes and 23 transmissions were identified by WGS. Transmission was the main mode of MDR-AB acquisition in our ICU. Our results demonstrated that WGS was a discriminatory technique for epidemiological healthcare-infection studies. The technique should greatly benefit the identification of epidemic situations and controlling transmission events in the near future.

Investigating the effect of an identified mutation within a critical site of PAS domain of WalK protein in a vancomycin-intermediate resistant Staphylococcus aureus by computational approaches

Background

Vancomycin-intermediate resistant Staphylococcus aureus (VISA) is becoming a common cause of nosocomial infections worldwide. VISA isolates are developed by unclear molecular mechanisms via mutations in several genes, including walKR. Although studies have verified some of these mutations, there are a few studies that pay attention to the importance of molecular modelling of mutations.

Method

For genomic and transcriptomic comparisons in a laboratory-derived VISA strain and its parental strain, Sanger sequencing and reverse transcriptase quantitative PCR (RT-qPCR) methods were used, respectively. After structural protein mapping of the detected mutation, mutation effects were analyzed using molecular computational approaches and crystal structures of related proteins.

Results

A mutation WalK-H364R was occurred in a functional zinc ion coordinating residue within the PAS domain in the VISA strain. WalK-H364R was predicted to destabilize protein and decrease WalK interactions with proteins and nucleic acids. The RT-qPCR method showed downregulation of walKR, WalKR-regulated autolysins, and agr locus.

Conclusion

Overall, WalK-H364R mutation within a critical metal-coordinating site was presumably related to the VISA development. We assume that the WalK-H364R mutation resulted in deleterious effects on protein, which was verified by walKR gene expression changes.. Therefore, molecular modelling provides detailed insight into the molecular mechanism of VISA development, in particular, where allelic replacement experiments are not readily available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02298-9.

Acinetobacter baumannii Fatty Acid Desaturases Facilitate Survival in Distinct Environments

Maintaining optimal fluidity is essential to ensure adequate membrane structure and function under different environmental conditions. We apply integrated molecular approaches to characterize two desaturases (DesA and DesB) and define their specific roles in unsaturated fatty acid (UFA) production in Acinetobacter baumannii. Using a murine model, we reveal DesA to play a minor role in colonization of the respiratory tract, whereas DesB is important during invasive disease. Furthermore, using transcriptomic and bioinformatic analyses, a global regulator involved in fatty acid homeostasis and members of its regulon are characterized. Collectively, we show that DesA and DesB are primary contributors to UFA production in A. baumannii with infection studies illustrating that these distinct desaturases aid in the bacterium's ability to survive in multiple host niches. Hence, this study provides novel insights into the fundamentals of A. baumannii lipid biology, which contributes to the versatility of this critical bacterial pathogen.

Laboratory evolution of Mycobacterium on agar plates for analysis of resistance acquisition and drug sensitivity profiles

Drug-resistant tuberculosis (TB) is a growing public health problem. There is an urgent need for information regarding cross-resistance and collateral sensitivity relationships among drugs and the genetic determinants of anti-TB drug resistance for developing strategies to suppress the emergence of drug-resistant pathogens. To identify mutations that confer resistance to anti-TB drugs in Mycobacterium species, we performed the laboratory evolution of nonpathogenic Mycobacterium smegmatis, which is closely related to Mycobacterium tuberculosis, against ten anti-TB drugs. Next, we performed whole-genome sequencing and quantified the resistance profiles of each drug-resistant strain against 24 drugs. We identified the genes with novel meropenem (MP) and linezolid (LZD) resistance-conferring mutation, which also have orthologs, in M. tuberculosis H37Rv. Among the 240 possible drug combinations, we identified 24 pairs that confer cross-resistance and 18 pairs that confer collateral sensitivity. The acquisition of bedaquiline or linezolid resistance resulted in collateral sensitivity to several drugs, while the acquisition of MP resistance led to multidrug resistance. The MP-evolved strains showed cross-resistance to rifampicin and clarithromycin owing to the acquisition of a mutation in the intergenic region of the Rv2864c ortholog, which encodes a penicillin-binding protein, at an early stage. These results provide a new insight to tackle drug-resistant TB.

QPX7728, An Ultra-Broad-Spectrum B-Lactamase Inhibitor for Intravenous and Oral Therapy: Overview of Biochemical and Microbiological Characteristics

QPX7728 is a novel β-lactamase inhibitor (BLI) that belongs to a class of cyclic boronates. The first member of this class, vaborbactam, is a BLI in the recently approved Vabomere (meropenem-vaborbactam). In this paper we provide the overview of the biochemical, structural and microbiological studies that were recently conducted with QPX7728. We show that QPX7728 is an ultra-broad-spectrum β-lactamase inhibitor with the broadest spectrum of inhibition reported to date in a single BLI molecule; in addition to potent inhibition of clinically important serine β-lactamases, including Class A and D carbapenemases from Enterobacterales and notably, diverse Class D carbapenemases from Acinetobacter, it also inhibits many metallo β-lactamases. Importantly, it is minimally affected by general intrinsic resistance mechanisms such as efflux and porin mutations that impede entry of drugs into gram-negative bacteria. QPX7728 combinations with several intravenous (IV) β-lactam antibiotics shows broad coverage of Enterobacterales, Acinetobacter baumannii and Pseudomonas aeruginosa, including strains that are resistant to other IV β-lactam-BLI combinations, e.g., ceftazidime-avibactam, ceftolozane-tazobactam, meropenem-vaborbactam and imipenem-relebactam that were recently approved for clinical use. Based on studies with P. aeruginosa, different partner β-lactams in combination with QPX7728 may be optimal for the coverage of susceptible organisms. This provides microbiological justification for a stand-alone BLI product for co-administration with different β-lactams. QPX7728 can also be delivered orally; thus, its ultra-broad β-lactamase inhibition spectrum and other features could be also applied to oral QPX7728-based combination products. Clinical development of QPX7728 has been initiated.

mmCSM-PPI: predicting the effects of multiple point mutations on protein-protein interactions

Protein-protein interactions play a crucial role in all cellular functions and biological processes and mutations leading to their disruption are enriched in many diseases. While a number of computational methods to assess the effects of variants on protein-protein binding affinity have been proposed, they are in general limited to the analysis of single point mutations and have been shown to perform poorly on independent test sets. Here, we present mmCSM-PPI, a scalable and effective machine learning model for accurately assessing changes in protein-protein binding affinity caused by single and multiple missense mutations. We expanded our well-established graph-based signatures in order to capture physicochemical and geometrical properties of multiple wild-type residue environments and integrated them with substitution scores and dynamics terms from normal mode analysis. mmCSM-PPI was able to achieve a Pearson's correlation of up to 0.75 (RMSE = 1.64 kcal/mol) under 10-fold cross-validation and 0.70 (RMSE = 2.06 kcal/mol) on a non-redundant blind test, outperforming existing methods. Our method is freely available as a user-friendly and easy-to-use web server and API at http://biosig.unimelb.edu.au/mmcsm_ppi.

Ever-Adapting RND Efflux Pumps in Gram-Negative Multidrug-Resistant Pathogens: A Race against Time

The rise in multidrug resistance (MDR) is one of the greatest threats to human health worldwide. MDR in bacterial pathogens is a major challenge in healthcare, as bacterial infections are becoming untreatable by commercially available antibiotics. One of the main causes of MDR is the over-expression of intrinsic and acquired multidrug efflux pumps, belonging to the resistance-nodulation-division (RND) superfamily, which can efflux a wide range of structurally different antibiotics. Besides over-expression, however, recent amino acid substitutions within the pumps themselves-causing an increased drug efflux efficiency-are causing additional worry. In this review, we take a closer look at clinically, environmentally and laboratory-evolved Gram-negative bacterial strains and their decreased drug sensitivity as a result of mutations directly in the RND-type pumps themselves (from Escherichia coli, Salmonella enterica, Neisseria gonorrhoeae, Pseudomonas aeruginosa, Acinetobacter baumannii and Legionella pneumophila). We also focus on the evolution of the efflux pumps by comparing hundreds of efflux pumps to determine where conservation is concentrated and where differences in amino acids can shed light on the broad and even broadening drug recognition. Knowledge of conservation, as well as of novel gain-of-function efflux pump mutations, is essential for the development of novel antibiotics and efflux pump inhibitors.

Distinguishing between PTEN clinical phenotypes through mutation analysis

Phosphate and tensin homolog on chromosome ten (PTEN) germline mutations are associated with an overarching condition known as PTEN hamartoma tumor syndrome. Clinical phenotypes associated with this syndrome range from macrocephaly and autism spectrum disorder to Cowden syndrome, which manifests as multiple noncancerous tumor-like growths (hamartomas), and an increased predisposition to certain cancers. It is unclear, however, the basis by which mutations might lead to these very diverse phenotypic outcomes. Here we show that, by considering the molecular consequences of mutations in PTEN on protein structure and function, we can accurately distinguish PTEN mutations exhibiting different phenotypes. Changes in phosphatase activity, protein stability, and intramolecular interactions appeared to be major drivers of clinical phenotype, with cancer-associated variants leading to the most drastic changes, while ASD and non-pathogenic variants associated with more mild and neutral changes, respectively. Importantly, we show via saturation mutagenesis that more than half of variants of unknown significance could be associated with disease phenotypes, while over half of Cowden syndrome mutations likely lead to cancer. These insights can assist in exploring potentially important clinical outcomes delineated by PTEN variation.

Acinetobacter baumannii Antibiotic Resistance Mechanisms

Acinetobacter baumannii is a Gram-negative ESKAPE microorganism that poses a threat to public health by causing severe and invasive (mostly nosocomial) infections linked with high mortality rates. During the last years, this pathogen displayed multidrug resistance (MDR), mainly due to extensive antibiotic abuse and poor stewardship. MDR isolates are associated with medical history of long hospitalization stays, presence of catheters, and mechanical ventilation, while immunocompromised and severely ill hosts predispose to invasive infections. Next-generation sequencing techniques have revolutionized diagnosis of severe A. baumannii infections, contributing to timely diagnosis and personalized therapeutic regimens according to the identification of the respective resistance genes. The aim of this review is to describe in detail all current knowledge on the genetic background of A. baumannii resistance mechanisms in humans as regards beta-lactams (penicillins, cephalosporins, carbapenems, monobactams, and beta-lactamase inhibitors), aminoglycosides, tetracyclines, fluoroquinolones, macrolides, lincosamides, streptogramin antibiotics, polymyxins, and others (amphenicols, oxazolidinones, rifamycins, fosfomycin, diaminopyrimidines, sulfonamides, glycopeptide, and lipopeptide antibiotics). Mechanisms of antimicrobial resistance refer mainly to regulation of antibiotic transportation through bacterial membranes, alteration of the antibiotic target site, and enzymatic modifications resulting in antibiotic neutralization. Virulence factors that may affect antibiotic susceptibility profiles and confer drug resistance are also being discussed. Reports from cases of A. baumannii coinfection with SARS-CoV-2 during the COVID-19 pandemic in terms of resistance profiles and MDR genes have been investigated.

Common Adaptive Strategies Underlie Within-Host Evolution of Bacterial Pathogens

Within-host adaptation is a hallmark of chronic bacterial infections, involving substantial genomic changes. Recent large-scale genomic data from prolonged infections allow the examination of adaptive strategies employed by different pathogens and open the door to investigate whether they converge toward similar strategies. Here, we compiled extensive data of whole-genome sequences of bacterial isolates belonging to miscellaneous species sampled at sequential time points during clinical infections. Analysis of these data revealed that different species share some common adaptive strategies, achieved by mutating various genes. Although the same genes were often mutated in several strains within a species, different genes related to the same pathway, structure, or function were changed in other species utilizing the same adaptive strategy (e.g., mutating flagellar genes). Strategies exploited by various bacterial species were often predicted to be driven by the host immune system, a powerful selective pressure that is not species specific. Remarkably, we find adaptive strategies identified previously within single species to be ubiquitous. Two striking examples are shifts from siderophore-based to heme-based iron scavenging (previously shown for Pseudomonas aeruginosa) and changes in glycerol-phosphate metabolism (previously shown to decrease sensitivity to antibiotics in Mycobacterium tuberculosis). Virulence factors were often adaptively affected in different species, indicating shifts from acute to chronic virulence and virulence attenuation during infection. Our study presents a global view on common within-host adaptive strategies employed by different bacterial species and provides a rich resource for further studying these processes.

ThermoMutDB: a thermodynamic database for missense mutations

Proteins are intricate, dynamic structures, and small changes in their amino acid sequences can lead to large effects on their folding, stability and dynamics. To facilitate the further development and evaluation of methods to predict these changes, we have developed ThermoMutDB, a manually curated database containing >14,669 experimental data of thermodynamic parameters for wild type and mutant proteins. This represents an increase of 83% in unique mutations over previous databases and includes thermodynamic information on 204 new proteins. During manual curation we have also corrected annotation errors in previously curated entries. Associated with each entry, we have included information on the unfolding Gibbs free energy and melting temperature change, and have associated entries with available experimental structural information. ThermoMutDB supports users to contribute to new data points and programmatic access to the database via a RESTful API. ThermoMutDB is freely available at: http://biosig.unimelb.edu.au/thermomutdb.

HARP: a database of structural impacts of systematic missense mutations in drug targets of Mycobacterium leprae

Computational Saturation Mutagenesis is an in-silico approach that employs systematic mutagenesis of each amino acid residue in the protein to all other amino acid types, and predicts changes in thermodynamic stability and affinity to the other subunits/protein counterparts, ligands and nucleic acid molecules. The data thus generated are useful in understanding the functional consequences of mutations in antimicrobial resistance phenotypes. In this study, we applied computational saturation mutagenesis to three important drug-targets in Mycobacterium leprae (M. leprae) for the drugs dapsone, rifampin and ofloxacin namely Dihydropteroate Synthase (DHPS), RNA Polymerase (RNAP) and DNA Gyrase (GYR), respectively. M. leprae causes leprosy and is an obligate intracellular bacillus with limited protein structural information associating mutations with phenotypic resistance outcomes in leprosy. Experimentally solved structures of DHPS, RNAP and GYR of M. leprae are not available in the Protein Data Bank, therefore, we modelled the structures of these proteins using template-based comparative modelling and introduced systematic mutations in each model generating 80,902 mutations and mutant structures for all the three proteins. Impacts of mutations on stability and protein-subunit, protein-ligand and protein-nucleic acid affinities were computed using various in-house developed and other published protein stability and affinity prediction software. A consensus impact was estimated for each mutation using qualitative scoring metrics for physicochemical properties and by a categorical grouping of stability and affinity predictions. We developed a web database named HARP (a database of Hansen's Disease Antimicrobial Resistance Profiles), which is accessible at the URL - https://harp-leprosy.org and provides the details to each of these predictions.

Multidrug-resistant Acinetobacter baumannii outbreaks: a global problem in healthcare settings

INTRODUCTION

The increase in the prevalence of multidrug-resistant Acinetobacter baumannii infections in hospital settings has rapidly emerged worldwide as a serious health problem.

METHODS

This review synthetizes the epidemiology of multidrug-resistant A. baumannii, highlighting resistance mechanisms.

CONCLUSIONS

Understanding the genetic mechanisms of resistance as well as the associated risk factors is critical to develop and implement adequate measures to control and prevent acquisition of nosocomial infections, especially in an intensive care unit setting.

Combining structure and genomics to understand antimicrobial resistance

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches

Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce protein affinities within the RNA polymerase complex, subsequently reducing nucleic acid affinity. Here, we have used these insights to develop a computational rifampicin resistance predictor capable of identifying resistant mutations even outside the well-defined rifampicin resistance determining region (RRDR), using clinical M. tuberculosis sequencing information. Our tool successfully identified up to 90.9% of M. tuberculosis rpoB variants correctly, with sensitivity of 92.2%, specificity of 83.6% and MCC of 0.69, outperforming the current gold-standard GeneXpert-MTB/RIF. We show our model can be translated to other clinically relevant organisms: M. leprae, P. aeruginosa and S. aureus, despite weak sequence identity. Our method was implemented as an interactive tool, SUSPECT-RIF (StrUctural Susceptibility PrEdiCTion for RIFampicin), freely available at https://biosig.unimelb.edu.au/suspect_rif/ .

In Vitro Activity of the Ultra-Broad-Spectrum Beta-Lactamase Inhibitor QPX7728 in Combination with Meropenem against Clinical Isolates of Carbapenem-Resistant Acinetobacter baumannii

QPX7728 is a recently discovered ultra-broad-spectrum beta-lactamase inhibitor (BLI) with potent inhibition of key serine and metallo-beta-lactamases. QPX7728 enhances the potency of many beta-lactams, including carbapenems, in beta-lactamase-producing Gram-negative bacteria, including Acinetobacter spp. The potency of meropenem alone and in combination with QPX7728 (1 to 16 μg/ml) was tested against 275 clinical isolates of Acinetobacter baumannii (carbapenem-resistant A. baumannii [CRAB]) collected worldwide that were highly resistant to carbapenems (MIC50 and MIC90 for meropenem, 64 and >64 μg/ml). Addition of QPX7728 resulted in a marked concentration-dependent increase in meropenem potency, with the MIC90 of meropenem alone decreasing from >64 μg/ml to 8 and 4 μg/ml when tested with fixed concentrations of QPX7728 at 4 and 8 μg/ml, respectively. In order to identify the mechanisms that modulate the meropenem-QPX7728 MIC, the whole-genome sequences were determined for 135 isolates with a wide distribution of meropenem-QPX7728 MICs. This panel of strains included 116 strains producing OXA carbapenemases (71 OXA-23, 16 OXA-72, 16 OXA-24, 9 OXA-58, and 4 OXA-239), 5 strains producing NDM-1, one KPC-producing strain, and 13 strains that did not carry any known carbapenemases but were resistant to meropenem (MIC ≥ 4 μg/ml). Our analysis indicated that mutated PBP3 (with mutations localized in the vicinity of the substrate/inhibitor binding site) is the main factor that contributes to the reduction of meropenem-QPX7728 potency. Still, >90% of isolates that carried PBP3 mutations remained susceptible to ≤8 μg/ml of meropenem when tested with a fixed 4 to 8 μg/ml of QPX7728. In the absence of PBP3 mutations, the MICs of meropenem tested in combination with 4 to 8 μg/ml of QPX7728 did not exceed 8 μg/ml. In the presence of both PBP3 and efflux mutations, 84.6% of isolates were susceptible to ≤8 μg/ml of meropenem with 4 or 8 μg/ml of QPX7728. The combination of QPX7728 with meropenem against CRAB isolates with multiple resistance mechanisms has an attractive microbiological profile.

mCSM-membrane: predicting the effects of mutations on transmembrane proteins

Significant efforts have been invested into understanding and predicting the molecular consequences of mutations in protein coding regions, however nearly all approaches have been developed using globular, soluble proteins. These methods have been shown to poorly translate to studying the effects of mutations in membrane proteins. To fill this gap, here we report, mCSM-membrane, a user-friendly web server that can be used to analyse the impacts of mutations on membrane protein stability and the likelihood of them being disease associated. mCSM-membrane derives from our well-established mutation modelling approach that uses graph-based signatures to model protein geometry and physicochemical properties for supervised learning. Our stability predictor achieved correlations of up to 0.72 and 0.67 (on cross validation and blind tests, respectively), while our pathogenicity predictor achieved a Matthew's Correlation Coefficient (MCC) of up to 0.77 and 0.73, outperforming previously described methods in both predicting changes in stability and in identifying pathogenic variants. mCSM-membrane will be an invaluable and dedicated resource for investigating the effects of single-point mutations on membrane proteins through a freely available, user friendly web server at http://biosig.unimelb.edu.au/mcsm_membrane.

mCSM-AB2: guiding rational antibody design using graph-based signatures

MOTIVATION

A lack of accurate computational tools to guide rational mutagenesis has made affinity maturation a recurrent challenge in antibody (Ab) development. We previously showed that graph-based signatures can be used to predict the effects of mutations on Ab binding affinity.

RESULTS

Here we present an updated and refined version of this approach, mCSM-AB2, capable of accurately modelling the effects of mutations on Ab-antigen binding affinity, through the inclusion of evolutionary and energetic terms. Using a new and expanded database of over 1800 mutations with experimental binding measurements and structural information, mCSM-AB2 achieved a Pearson's correlation of 0.73 and 0.77 across training and blind tests, respectively, outperforming available methods currently used for rational Ab engineering.

AVAILABILITY AND IMPLEMENTATION

mCSM-AB2 is available as a user-friendly and freely accessible web server providing rapid analysis of both individual mutations or the entire binding interface to guide rational antibody affinity maturation at http://biosig.unimelb.edu.au/mcsm_ab2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations

Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein structure and function. Approaches to estimate these changes have been proposed, but most only consider single‐point missense variants and a static state of the protein, with those that incorporate dynamics are computationally expensive. Here we present DynaMut2, a web server that combines Normal Mode Analysis (NMA) methods to capture protein motion and our graph‐based signatures to represent the wildtype environment to investigate the effects of single and multiple point mutations on protein stability and dynamics. DynaMut2 was able to accurately predict the effects of missense mutations on protein stability, achieving Pearson's correlation of up to 0.72 (RMSE: 1.02 kcal/mol) on a single point and 0.64 (RMSE: 1.80 kcal/mol) on multiple‐point missense mutations across 10‐fold cross‐validation and independent blind tests. For single‐point mutations, DynaMut2 achieved comparable performance with other methods when predicting variations in Gibbs Free Energy (ΔΔG) and in melting temperature (ΔT_m). We anticipate our tool to be a valuable suite for the study of protein flexibility analysis and the study of the role of variants in disease. DynaMut2 is freely available as a web server and API at http://biosig.unimelb.edu.au/dynamut2.

Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis

Mutations in protein-coding regions can lead to large biological changes and are associated with genetic conditions, including cancers and Mendelian diseases, as well as drug resistance. Although whole genome and exome sequencing help to elucidate potential genotype-phenotype correlations, there is a large gap between the identification of new variants and deciphering their molecular consequences. A comprehensive understanding of these mechanistic consequences is crucial to better understand and treat diseases in a more personalized and effective way. This is particularly relevant considering estimates that over 80% of mutations associated with a disease are incorrectly assumed to be causative. A thorough analysis of potential effects of mutations is required to correctly identify the molecular mechanisms of disease and enable the distinction between disease-causing and non-disease-causing variation within a gene. Here we present an overview of our integrative mutation analysis platform, which focuses on refining the current genotype-phenotype correlation methods by using the wealth of protein structural information.

mmCSM-AB: guiding rational antibody engineering through multiple point mutations

While antibodies are becoming an increasingly important therapeutic class, especially in personalized medicine, their development and optimization has been largely through experimental exploration. While there have been many efforts to develop computational tools to guide rational antibody engineering, most approaches are of limited accuracy when applied to antibody design, and have largely been limited to analysing a single point mutation at a time. To overcome this gap, we have curated a dataset of 242 experimentally determined changes in binding affinity upon multiple point mutations in antibody-target complexes (89 increasing and 153 decreasing binding affinity). Here, we have shown that by using our graph-based signatures and atomic interaction information, we can accurately analyse the consequence of multi-point mutations on antigen binding affinity. Our approach outperformed other available tools across cross-validation and two independent blind tests, achieving Pearson's correlations of up to 0.95. We have implemented our new approach, mmCSM-AB, as a web-server that can help guide the process of affinity maturation in antibody design. mmCSM-AB is freely available at http://biosig.unimelb.edu.au/mmcsm_ab/.

Structure guided prediction of Pyrazinamide resistance mutations in pncA

Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/.

A Comprehensive Computational Platform to Guide Drug Development Using Graph-Based Signature Methods

High-throughput computational techniques have become invaluable tools to help increase the overall success, process efficiency, and associated costs of drug development. By designing ligands tailored to specific protein structures in a disease of interest, an understanding of molecular interactions and ways to optimize them can be achieved prior to chemical synthesis. This understanding can help direct crucial chemical and biological experiments by maximizing available resources on higher quality leads. Moreover, predicting molecular binding affinity within specific biological contexts, as well as ligand pharmacokinetics and toxicities, can aid in filtering out redundant leads early on within the process. We describe a set of computational tools which can aid in drug discovery at different stages, from hit identification (EasyVS) to lead optimization and candidate selection (CSM-lig, mCSM-lig, Arpeggio, pkCSM). Incorporating these tools along the drug development process can help ensure that candidate leads are chemically and biologically feasible to become successful and tractable drugs.

Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning

Next-generation sequencing methods have not only allowed an understanding of genome sequence variation during the evolution of organisms but have also provided invaluable information about genetic variants in inherited disease and the emergence of resistance to drugs in cancers and infectious disease. A challenge is to distinguish mutations that are drivers of disease or drug resistance, from passengers that are neutral or even selectively advantageous to the organism. This requires an understanding of impacts of missense mutations in gene expression and regulation, and on the disruption of protein function by modulating protein stability or disturbing interactions with proteins, nucleic acids, small molecule ligands, and other biological molecules. Experimental approaches to understanding differences between wild-type and mutant proteins are most accurate but are also time-consuming and costly. Computational tools used to predict the impacts of mutations can provide useful information more quickly. Here, we focus on two widely used structure-based approaches, originally developed in the Blundell lab: site-directed mutator (SDM), a statistical approach to analyze amino acid substitutions, and mutation cutoff scanning matrix (mCSM), which uses graph-based signatures to represent the wild-type structural environment and machine learning to predict the effect of mutations on protein stability. Here, we describe DUET that uses machine learning to combine the two approaches. We discuss briefly the development of mCSM for understanding the impacts of mutations on interfaces with other proteins, nucleic acids, and ligands, and we exemplify the wide application of these approaches to understand human genetic disorders and drug resistance mutations relevant to cancer and mycobacterial infections. STATEMENT FOR A BROADER AUDIENCE: Genetic or somatic changes in genes can lead to mutations in human proteins, which give rise to genetic disorders or cancer, or to genes of pathogens leading to drug resistance. Computer software described here, using statistical approaches or machine learning, uses the information from genome sequencing of humans and pathogens, together with experimental or modeled 3D structures of gene products, the proteins, to predict impacts of mutations in genetic disease, cancer and drug resistance.

Multidrug Resistant Acinetobacter baumannii: Resistance by Any Other Name Would Still be Hard to Treat

PURPOSE OF REVIEW

Acinetobacter baumannii (AB) is an infamous nosocomial pathogen with a seemingly limitless capacity for antimicrobial resistance, leading to few treatment options and poor clinical outcomes. The debatably low pathogenicity and virulence of AB are juxtaposed by its exceptionally high rate of infection-related mortality, likely due to delays in time to effective antimicrobial therapy secondary to its predilection for resistance to first-line agents. Recent studies of AB and its infections have led to a burgeoning understanding of this critical microbial threat and provided clinicians with new ammunition for which to target this elusive pathogen. This review will provide an update on the virulence, resistance, diagnosis, and treatment of multidrug resistant (MDR) AB.

RECENT FINDINGS

Advances in bacterial genomics have led to a deeper understanding of the unique mechanisms of resistance often present in MDR AB and how they may be exploited by new antimicrobials or optimized combinations of existing agents. Further, improvements in rapid diagnostic tests (RDTs) and their more pervasive use in combination with antimicrobial stewardship interventions have allowed for more rapid diagnosis of AB and decreases in time to effective therapy. Unfortunately, there remains a paucity of high-quality clinical data for which to inform the optimal treatment of MDR AB infections. In fact, recently completed studies have failed to identify a combination regimen that is consistently superior to monotherapy, despite the benefits demonstrated in vitro. Encouragingly, new and updated guidelines offer strategies for the treatment of MDR AB and may help to harmonize the use of high toxicity agents such as the polymyxins. Finally, new antimicrobial agents such as eravacycline and cefiderocol have promising in vitro activity against MDR AB but their place in therapy for these infections remains to be determined. Notwithstanding available clinical trial data, polymyxin-based combination therapies with either a carbapenem, minocycline, or eravacycline remain the treatment of choice for MDR, particularly carbapenem-resistant, AB. Incorporating antimicrobial stewardship intervention with RDTs relevant to MDR AB can help avoid potentially toxic combination therapies and catalyze the most important modifiable risk factor for mortality-time to effective therapy. Further research efforts into pharmacokinetic/pharmacodynamic-based dose optimization and clinical outcomes data for MDR AB continue to be desperately needed.

Whole-Genome Sequencing to Differentiate Relapse From Reinfection in Community-Onset Bacteremic Acinetobacter baumannii Pneumonia

Community-onset bacteremic Acinetobacter baumannii pneumonia recurred in 3 of 30 (10%) patients followed prospectively, all with ongoing hazardous alcohol intake, 3-56 months after initial pneumonia. Paired isolates underwent whole-genome sequencing. Phylogenetic analysis showed that recurrence strains were all distinct from preceding strains, indicating reinfection in susceptible individuals rather than relapse.

Empirical ways to identify novel Bedaquiline resistance mutations in AtpE

Clinical resistance against Bedaquiline, the first new anti-tuberculosis compound with a novel mechanism of action in over 40 years, has already been detected in Mycobacterium tuberculosis. As a new drug, however, there is currently insufficient clinical data to facilitate reliable and timely identification of genomic determinants of resistance. Here we investigate the structural basis for M. tuberculosis associated bedaquiline resistance in the drug target, AtpE. Together with the 9 previously identified resistance-associated variants in AtpE, 54 non-resistance-associated mutations were identified through comparisons of bedaquiline susceptibility across 23 different mycobacterial species. Computational analysis of the structural and functional consequences of these variants revealed that resistance associated variants were mainly localized at the drug binding site, disrupting key interactions with bedaquiline leading to reduced binding affinity. This was used to train a supervised predictive algorithm, which accurately identified likely resistance mutations (93.3% accuracy). Application of this model to circulating variants present in the Asia-Pacific region suggests that current circulating variants are likely to be susceptible to bedaquiline. We have made this model freely available through a user-friendly web interface called SUSPECT-BDQ, StrUctural Susceptibility PrEdiCTion for bedaquiline (http://biosig.unimelb.edu.au/suspect_bdq/). This tool could be useful for the rapid characterization of novel clinical variants, to help guide the effective use of bedaquiline, and to minimize the spread of clinical resistance.

Involvement of the RND efflux pump transporter SmeH in the acquisition of resistance to ceftazidime in Stenotrophomonas maltophilia

The emergence of antibiotic resistant Gram-negative bacteria has become a serious global health issue. In this study, we have employed the intrinsically resistant opportunistic pathogen Stenotrophomonas maltophilia as a model to study the mechanisms involved in the acquisition of mutation-driven resistance to antibiotics. To this aim, laboratory experimental evolution studies, followed by whole-genome sequencing, were performed in the presence of the third-generation cephalosporin ceftazidime. Using this approach, we determined that exposure to increasing concentrations of ceftazidime selects high-level resistance in S. maltophilia through a novel mechanism: amino acid substitutions in SmeH, the transporter protein of the SmeGH RND efflux pump. The recreation of these mutants in a wild-type background demonstrated that, in addition to ceftazidime, the existence of these substitutions provides bacteria with cross-resistance to other beta-lactam drugs. This acquired resistance does not impose relevant fitness costs when bacteria grow in the absence of antibiotics. Structural prediction of both amino acid residues points that the observed resistance phenotype could be driven by changes in substrate access and recognition.

Exploring Protein Supersecondary Structure Through Changes in Protein Folding, Stability, and Flexibility

The ability to predict how mutations affect protein structure, folding, and flexibility can elucidate the molecular mechanisms leading to disruption of supersecondary structures, the emergence of phenotypes, as well guiding rational protein engineering. The advent of fast and accurate computational tools has enabled us to comprehensively explore the landscape of mutation effects on protein structures, prioritizing mutations for rational experimental validation.Here we describe the use of two complementary web-based in silico methods, DUET and DynaMut, developed to infer the effects of mutations on folding, stability, and flexibility and how they can be used to explore and interpret these effects on protein supersecondary structures.