Antibiotic resistance poses a significant threat to global public health due to complex interactions between bacterial genetic factors and external influences such as antibiotic misuse. Artificial intelligence (AI) offers innovative strategies to address this crisis. For example, AI can analyze genomic data to detect resistance markers early on, enabling early interventions. In addition, AI-powered decision support systems can optimize antibiotic use by recommending the most effective treatments based on patient data and local resistance patterns. AI can accelerate drug discovery by predicting the efficacy of new compounds and identifying potential antibacterial agents. Although progress has been made, challenges persist, including data quality, model interpretability, and real-world implementation. A multidisciplinary approach that integrates AI with other emerging technologies, such as synthetic biology and nanomedicine, could pave the way for effective prevention and mitigation of antimicrobial resistance, preserving the efficacy of antibiotics for future generations.

[This corrects the article DOI: 10.3389/fimmu.2022.921483.].

In his 1945 Nobel Prize acceptance speech, Sir Alexander Fleming warned of antimicrobial resistance (AMR) if the necessary precautions were not taken diligently. As the growing threat of AMR continues to loom over humanity, we must look forward to alternative diagnostic tools and preventive measures to thwart looming economic collapse and untold mortality worldwide. The integration of machine learning (ML) methodologies within the framework of such tools/pipelines presents a promising avenue, offering unprecedented insights into the underlying mechanisms of resistance and enabling the development of more targeted and effective treatments. This paper explores the applications of ML in predicting and understanding AMR, highlighting its potential in revolutionizing healthcare practices. From the utilization of supervised-learning approaches to analyze genetic signatures of antibiotic resistance to the development of tools and databases, such as the Comprehensive Antibiotic Resistance Database (CARD), ML is actively shaping the future of AMR research. However, the successful implementation of ML in this domain is not without challenges. The dependence on high-quality data, the risk of overfitting, model selection, and potential bias in training data are issues that must be systematically addressed. Despite these challenges, the synergy between ML and biomedical research shows great promise in combating the growing menace of antibiotic resistance.

OBJECTIVE: New approaches are needed to discover novel antimicrobials, particularly antibiotics that target the Gram-negative outer membrane. By exploiting bacterial sensing and responses to outer membrane (OM) damage, we used a biosensor approach consisting of polymyxin resistance gene transcriptional reporters to screen natural products and a small drug library for biosensor activity that indicates damage to the OM. The diverse antimicrobial compounds that cause induction of the polymyxin resistance genes, which correlates with outer membrane damage, suggest that these LPS and surface modifications also function in short-term repair to sublethal exposure and are required against broad membrane stress conditions.

The lack of available treatments for many antimicrobial-resistant infections highlights the critical need for antibiotic discovery innovation. Peptides are an underappreciated antibiotic scaffold because they often suffer from proteolytic instability and toxicity toward human cells, making in vivo use challenging. To investigate sequence factors related to serum activity, we adapt an antibacterial display technology to screen a library of peptide macrocycles for antibacterial potential directly in human serum. We identify dozens of new macrocyclic peptide antibiotic sequences and find that serum activity within our library is influenced by peptide length, cationic charge, and the number of disulfide bonds present. Interestingly, an optimized version of our most active lead peptide permeates the outer membrane of Gram-negative bacteria without strong inner-membrane disruption and kills bacteria slowly while causing cell elongation. This contrasts with traditional cationic antimicrobial peptides, which kill rapidly via lysis of both bacterial membranes. Notably, this optimized variant is not toxic to mammalian cells and retains its function in vivo, suggesting therapeutic promise. Our results support the use of more physiologically relevant conditions when screening peptides for antimicrobial activity which retain in vivo functionality.

Gram-negative bacteria are uniquely equipped to defeat antibiotics. Their outermost layer, the cell envelope, is a natural permeability barrier that contains an array of resistance proteins capable of neutralizing most existing antimicrobials. As a result, its presence creates a major obstacle for the treatment of resistant infections and for the development of new antibiotics. Despite this seemingly impenetrable armor, in-depth understanding of the cell envelope, including structural, functional and systems biology insights, has promoted efforts to target it that can ultimately lead to the generation of new antibacterial therapies. In this article, we broadly overview the biology of the cell envelope and highlight attempts and successes in generating inhibitors that impair its function or biogenesis. We argue that the very structure that has hampered antibiotic discovery for decades has untapped potential for the design of novel next-generation therapeutics against bacterial pathogens.

Global antimicrobial resistance is a health crisis that can change the face of modern medicine. Exploring diverse natural habitats for bacterially-derived novel antimicrobial compounds has historically been a successful strategy. The deep-sea presents an exciting opportunity for the cultivation of taxonomically novel organisms and exploring potentially chemically novel spaces. In this study, the draft genomes of 12 bacteria previously isolated from the deep-sea sponges Phenomena carpenteri and Hertwigia sp. are investigated for the diversity of specialized secondary metabolites. In addition, early data support the production of antibacterial inhibitory substances produced from a number of these strains, including activity against clinically relevant pathogens Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus. Draft whole-genomes are presented of 12 deep-sea isolates, which include four potentially novel strains: Psychrobacter sp. PP-21, Streptomyces sp. DK15, Dietzia sp. PP-33, and Micrococcus sp. M4NT. Across the 12 draft genomes, 138 biosynthetic gene clusters were detected, of which over half displayed less than 50% similarity to known BGCs, suggesting that these genomes present an exciting opportunity to elucidate novel secondary metabolites. Exploring bacterial isolates belonging to the phylum Actinomycetota, Pseudomonadota, and Bacillota from understudied deep-sea sponges provided opportunities to search for new chemical diversity of interest to those working in antibiotic discovery.

Antimicrobial compounds, including antibiotics, have been a cornerstone of modern medicine being able to both treat infections and prevent infections in at-risk people, including those who are immune-compromised and those undergoing routine surgical procedures. Their intense use, including in people, animals, and plants, has led to an increase in the incidence of resistant bacteria and fungi, resulting in a desperate need for novel antimicrobial compounds with new mechanisms of action. Many antimicrobial compounds in current use originate from microbial sources, such as penicillin from the fungus Penicillium chrysogenum (renamed by some as P. rubens). Through a collaboration with Aotearoa New Zealand Crown Research Institute Manaaki Whenua-Landcare Research we have access to a collection of thousands of fungal cultures known as the International Collection of Microorganisms from Plants (ICMP). The ICMP contains both known and novel species which have not been extensively tested for their antimicrobial activity. Initial screening of ICMP isolates for activity against Escherichia coli and Staphylococcus aureus directed our interest towards ICMP 477, an isolate of the soil-inhabiting fungus, Aspergillus terreus. In our investigation of the secondary metabolites of A. terreus, through extraction, fractionation, and purification, we isolated nine known natural products. We evaluated the biological activity of selected compounds against various bacteria and fungi and discovered that terrein (1) has potent activity against the important human pathogen Cryptococcus neoformans.

Although COVID-19 has captured most of the public health attention, antimicrobial resistance (AMR) has not disappeared. To prevent the escape of resistant microorganisms in animals or environmental reservoirs a \"one health approach\" is desirable. In this context of COVID-19, AMR has probably been affected by the inappropriate or over-use of antibiotics. The increased use of antimicrobials and biocides for disinfection may have enhanced the prevalence of AMR. Antibiotics have been used empirically in patients with COVID-19 to avoid or prevent bacterial coinfection or superinfections. On the other hand, the measures to prevent the transmission of COVID-19 could have reduced the risk of the emergence of multidrug-resistant microorganisms. Since we do not currently have a sterilizing vaccine against SARS-CoV-2, the virus may still multiply in the organism and new mutations may occur. As a consequence, there is a risk of the appearance of new variants. Nature-derived anti-infective agents, such as antibodies and antimicrobial peptides (AMPs), are very promising in the fight against infectious diseases, because they are less likely to develop resistance, even though further investigation is still required.

The golden age of antibiotic discovery in the 1940s-1960s saw the development and deployment of many different classes of antibiotics, revolutionizing the field of medicine. Since that time, our ability to discover antibiotics of novel structural classes or mechanisms has not kept pace with the ever-growing threat of antibiotic resistance. Recently, advances at the intersection of genomics and chemical biology have enabled efforts to better define the vulnerabilities of essential gene targets, to develop sophisticated whole-cell chemical screening methods that reveal target biology early, and to elucidate small molecule targets and modes of action more effectively. These new technologies have the potential to expand the chemical diversity of antibiotic candidates, as well as the breadth of targets. We illustrate how the latest tools of genomics and chemical biology are being integrated to better understand pathogen vulnerabilities and antibiotic mechanisms in order to inform a new era of antibiotic discovery.