In the 20th century, the development, licensing and implementation of vaccines as part of large, systematic immunization programs started to address health inequities that existed globally. However, at the time of writing, access to vaccines that prevent life-threatening infectious diseases remains unequal to all infants, children and adults in the world. This is a problem that many individuals and agencies are working hard to address globally. As clinicians and biomedical scientists we often focus on the health benefits that vaccines provide, in the prevention of ill-health and death from infectious pathogens. Here we discuss the health, economic and social benefits of vaccines that have been identified and studied in recent years, impacting all regions and all age groups. After learning of the emergence of SARS-CoV-2 virus in December 2019, and its potential for global dissemination to cause COVID-19 disease was realized, there was an urgent need to develop vaccines at an unprecedented rate and scale. As we appreciate and quantify the health, economic and social benefits of vaccines and immunization programs to individuals and society, we should endeavor to communicate this to the public and policy makers, for the benefit of endemic, epidemic, and pandemic diseases.

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Impact of Vaccines; Health, Economic and Social Perspectives

Antimicrobial resistance (AMR) is the major issue posing a serious global health threat. Low- and middle-income countries are likely to be the most affected, both in terms of impact on public health and economic burden. Recent studies highlighted the role of resistance networks on the transmission of AMR organisms, with this network being driven by complex interactions between clinical (e.g., human health, animal husbandry and veterinary medicine) and other components, including environmental factors (e.g., persistence of AMR in wastewater). Many studies have highlighted the role of wastewater as a significant environmental reservoir of AMR as it represents an ideal environment for AMR bacteria (ARB) and antimicrobial resistant genes (ARGs) to persist. Although the treatment process can help in removing or reducing the ARB load, it has limited impact on ARGs. ARGs are not degradable; therefore, they can be spread among microbial communities in the environment through horizontal gene transfer, which is the main resistance mechanism in most Gram-negative bacteria. Here we analysed the recent literature to highlight the contribution of wastewater to the emergence, persistence and transmission of AMR under different settings, particularly those associated with mass gathering events (e.g., Hajj and Kumbh Mela).

The Contribution of Wastewater to the Transmission of Antimicrobial Resistance in the Environment: Implications of Mass Gathering Settings.

The Asia Pacific region, home to two-thirds of the world’s population and ten of the least developed countries, is considered a regional hot-spot for the emergence and spread of antimicrobial resistance (AMR). Despite this, there is a dearth of high-quality regional data on the extent of AMR. Recognising the urgency to close this gap, Singapore organised a meeting to discuss the problems in the region and frame a call for action. Representatives from across the region and beyond attended the meeting on the “Antimicrobial Resistance in the Asia Pacific & its impact on Singapore” held in November 2018. This meeting report is a summary of the discussions on the challenges and progress in surveillance, drivers and levers of AMR emergence, and the promising innovations and technologies that could be used to combat the increasing threat of AMR in the region. Enhanced surveillance and research to provide improved evidence-based strategies and policies are needed. The major themes that emerged for an action plan are working towards a tailored solution for the region by harnessing the One Health approach, enhancing inter-country collaborations, and collaboratively leverage upon new emerging technologies. A regionally coordinated effort that is target-driven, sustainable and builds on a framework facilitating communication and governance will strengthen the fight against AMR in the Asia Pacific region.

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Antimicrobial Resistance in the Asia Pacific region: a meeting report.

Reciprocal, intimate relationships between the human microbiome and the host immune system are shaped by past microbial encounters and prepare the host for future ones. Antibiotics and other antimicrobials leave their mark on both the microbiome and host immunity. Antimicrobials alter the structure of the microbiota, expand the host-specific pool of antimicrobial-resistance genes and organisms, degrade the protective effects of the microbiota against invasion by pathogens, and may impair vaccine efficacy. Through these effects on the microbiome they may affect immune responses. Vaccines that exert protective or therapeutic effects against pathogens may reduce the use of antimicrobials, the development and spread of antimicrobial resistance, and the harmful impacts of these drugs on the microbiome. Other strategies involving manipulation of the microbiome to deplete antibiotic-resistant organisms or to enhance immune responses to vaccines may prove valuable in addressing antimicrobial resistance as well. This article describes the intersections of immunity, microbiome and antimicrobial exposure, and the use of vaccines and other alternative strategies for the control and management of antimicrobial resistance.

https://www.pnas.org/content/pnas/115/51/12902.full.pdf

Microbiome as a tool and a target in the effort to address antimicrobial resistance.

Although the diversity of microbial communities (microbiota) inhabiting body niches are of proven importance to health in both humans and non-human animals, the functional importance of these collective genomes (microbiome) to the adaptive potential of their hosts has only recently been considered within a conservation framework. If loss of gut biodiversity threatens the health (and therefore the fitness of individuals), and this loss can be correlated with the adaptive potential of a species in changing environments, measuring functional composition of the microbiota from non-invasive samples, such as faeces and skin swabs, could provide a useful and practical tool for determining conservation priorities. This article reviews the evidence for adaptive potential of microbiota in wild species, and proposes future directions. While there is ample indication of inter- and intra-specific variation in microbiota diversity, there is little evidence that diversity per se confers fitness. However, there are convincing examples showing that microbiota flexibility, composition and function may well be sources of adaptive potential, although case studies are relatively few, and the analytical approaches needed to demonstrate the mechanisms underlying host–microbiota interactions have only recently been developed.

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Conserve the germs: the gut microbiota and adaptive potential

Ubiquitous in nature, antimicrobial resistance (AMR) has existed long before the golden age of antimicrobials. While antimicrobial agents are beneficial to combat infection, their widespread use contributes to the increase in and emergence of novel resistant microbes in virtually all environmental niches. The human microbiome is an important reservoir of AMR with initial exposure occurring in early life. Once seeded with AMR, commensal organisms may be key contributors to the dissemination of resistance due to the interconnectedness of microbial communities. When acquired by pathogens however, AMR becomes a serious public health threat worldwide. Our ability to combat the threat of emerging resistance relies on accurate AMR detection methods and the development of therapeutics that function despite the presence of antimicrobial resistance.

The Threat of Antimicrobial Resistance on the Human Microbiome

Next-generation sequencing technologies have generated, and continue to produce, an increasingly large corpus of biological data. The data generated are inherently compositional as they convey only relative information dependent upon the capacity of the instrument, experimental design and technical bias. There is considerable information to be gained through network analysis by studying the interactions between components within a system. Network theory methods using compositional data are powerful approaches for quantifying relationships between biological components and their relevance to phenotype, environmental conditions or other external variables. However, many of the statistical assumptions used for network analysis are not designed for compositional data and can bias downstream results. In this mini-review, we illustrate the utility of network theory in biological systems and investigate modern techniques while introducing researchers to frameworks for implementation. We overview (1) compositional data analysis, (2) data transformations and (3) network theory along with insight on a battery of network types including static-, temporal-, sample-specific- and differential-networks. The intention of this mini-review is not to provide a comprehensive overview of network methods, rather to introduce microbiology researchers to (semi)-unsupervised data-driven approaches for inferring latent structures that may give insight into biological phenomena or abstract mechanics of complex systems.

https://sfamjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/1462-2920.15091

Applications of weighted association networks applied to compositional data in biology.

To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demonstrates a need for approaches that accurately identify potential novelty with higher throughput and reduced labor. Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 known antibiotics and 9 crude extracts while depositing 122 transcriptomes unique to this study. Our CoHEC model can properly predict the primary MOA of previously unobserved compounds in both purified forms and crude extracts at an accuracy above 99%, while also correctly identifying darobactin, a newly discovered antibiotic, as having a novel MOA. In addition, we deploy our methods on a recent E. coli transcriptomics dataset from a different strain and a Mycobacterium smegmatis metabolomics timeseries dataset showcasing exceptionally high performance; improving upon the performance metrics of the original publications. We not only provide insight into the biological interpretation of our model but also that the concept of MOA is a non-discrete heuristic with diverse effects for different compounds within the same MOA, suggesting substantial antibiotic diversity awaiting discovery within existing MOA.

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Karen E. Nelson

Papers

The Threat of Antimicrobial Resistance on the Human Microbiome

Applications of weighted association networks applied to compositional data in biology.

Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach.