Natural products from reconstructed bacterial genomes of the Middle and Upper Paleolithic

Inferring diet, disease and antibiotic resistance from ancient human oral microbiomes

The interaction between a host and its microbiome is an area of intense study. For the human host, it is known that the various body-site-associated microbiomes impact heavily on health and disease states. For instance, the oral microbiome is a source of various pathogens and potential antibiotic resistance gene pools. The effect of historical changes to the human host and environment to the associated microbiome, however, has been less well explored. In this review, we characterize several historical and prehistoric events which are considered to have impacted the oral environment and therefore the bacterial communities residing within it. The link between evolutionary changes to the oral microbiota and the significant societal and behavioural changes occurring during the pre-Neolithic, Agricultural Revolution, Industrial Revolution and Antibiotic Era is outlined. While previous studies suggest the functional profile of these communities may have shifted over the centuries, there is currently a gap in knowledge that needs to be filled. Biomolecular archaeological evidence of innate antimicrobial resistance within the oral microbiome shows an increase in the abundance of antimicrobial resistance genes since the advent and widespread use of antibiotics in the modern era. Nevertheless, a lack of research into the prevalence and evolution of antimicrobial resistance within the oral microbiome throughout history hinders our ability to combat antimicrobial resistance in the modern era.

A Journey into the Evolution of Human Host-Oral Microbiome Relationship through Ancient Dental Calculus: A Scoping Review

One of the most promising areas of research in palaeomicrobiology is the study of the human microbiome. In particular, ancient dental calculus helps to reconstruct a substantial share of oral microbiome composition by mapping together human evolution with its state of health/oral disease. This review aims to trace microbial characteristics in ancient dental calculus to describe the evolution of the human host-oral microbiome relationship in oral health or disease in children and adults. Following the PRISMA-Extension for Scoping Reviews guidelines, the main scientific databases (PubMed, Scopus, Lilacs, Cochrane Library) have been drawn upon. Eligibility criteria were established, and all the data collected on a purpose-oriented collection form were analysed descriptively. From the initial 340 records, only 19 studies were deemed comprehensive enough for the purpose of this review. The knowledge of the composition of ancient oral microbiomes has broadened over the past few years thanks to increasingly well-performing decontamination protocols and additional analytical avenues. Above all, metagenomic sequencing, also implemented by state-of-the-art bioinformatics tools, allows for the determination of the qualitative-quantitative composition of microbial species associated with health status and caries/periodontal disease. Some microbial species, especially periodontal pathogens, do not appear to have changed in history, while others that support caries disease or oral health could be connected to human evolution through lifestyle and environmental contributing factors.

Benchmarking a targeted 16S ribosomal RNA gene enrichment approach to reconstruct ancient microbial communities

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Concise and collective total syntheses of 2,4-disubstituted furan-derived natural products from hydroxyoxetanyl ketones

The furan moiety, prevalent in bioactive natural products and essential drugs, presents intriguing structural features that have spurred our exploration into streamlined chemical synthesis routes for related natural products. In this study, we demonstrate the concise total synthesis of eight 2,4-disubstituted furan-derived natural products (including methylfuroic acid, rabdoketones A and B, paleofurans A and B, tournefolin C, and shikonofurans A and B). Our methodology revolves around the utilization of hydroxyoxetanyl ketones as pivotal intermediates. The approach encompasses transformations such as selective organo-catalyzed cross-ketol addition, synthesis of hydroxymethyl-tethered furans through Bi(OTf)3 catalyzed dehydrative cycloisomerization of α-hydroxyoxetanyl ketones, and a hydrogen atom transfer (HAT)-mediated oxidation of primary alcohols into the corresponding acids. This comprehensive synthetic strategy highlights the versatility of hydroxyoxetanyl ketones as invaluable building blocks in the synthesis of furan-containing natural products.

Paleomicrobiology: Tracking the past microbial life from single species to entire microbial communities

By deciphering information encoded in degraded ancient DNA extracted from up to million-years-old samples, molecular paleomicrobiology enables to objectively retrace the temporal evolution of microbial species and communities. Assembly of full-length genomes of ancient pathogen lineages allows not only to follow historical epidemics in space and time but also to identify the acquisition of genetic features that represent landmarks in the evolution of the host-microbe interaction. Analysis of microbial community DNA extracted from essentially human paleo-artefacts (paleofeces, dental calculi) evaluates the relative contribution of diet, lifestyle and geography on the taxonomic and functional diversity of these guilds in which have been identified species that may have gone extinct in today's human microbiome. As for non-host-associated environmental samples, such as stratified sediment cores, analysis of their DNA illustrates how and at which pace microbial communities are affected by local or widespread environmental disturbance. Description of pre-disturbance microbial diversity patterns can aid in evaluating the relevance and effectiveness of remediation policies. We finally discuss how recent achievements in paleomicrobiology could contribute to microbial biotechnology in the fields of medical microbiology and food science to trace the domestication of microorganisms used in food processing or to illustrate the historic evolution of food processing microbial consortia.

Resurrecting ancestral antibiotics: unveiling the origins of modern lipid II targeting glycopeptides

Antibiotics are central to modern medicine, and yet they are mainly the products of intra and inter-kingdom evolutionary warfare. To understand how nature evolves antibiotics around a common mechanism of action, we investigated the origins of an extremely valuable class of compounds, lipid II targeting glycopeptide antibiotics (GPAs, exemplified by teicoplanin and vancomycin), which are used as last resort for the treatment of antibiotic resistant bacterial infections. Using a molecule-centred approach and computational techniques, we first predicted the nonribosomal peptide synthetase assembly line of paleomycin, the ancestral parent of lipid II targeting GPAs. Subsequently, we employed synthetic biology techniques to produce the predicted peptide and validated its antibiotic activity. We revealed the structure of paleomycin, which enabled us to address how nature morphs a peptide antibiotic scaffold through evolution. In doing so, we obtained temporal snapshots of key selection domains in nonribosomal peptide synthesis during the biosynthetic journey from ancestral, teicoplanin-like GPAs to modern GPAs such as vancomycin. Our study demonstrates the synergy of computational techniques and synthetic biology approaches enabling us to journey back in time, trace the temporal evolution of antibiotics, and revive these ancestral molecules. It also reveals the optimisation strategies nature has applied to evolve modern GPAs, laying the foundation for future efforts to engineer this important class of antimicrobial agents.

aMeta: an accurate and memory-efficient ancient metagenomic profiling workflow

Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMeta, an accurate metagenomic profiling workflow for ancient DNA designed to minimize the amount of false discoveries and computer memory requirements. Using simulated data, we benchmark aMeta against a current state-of-the-art workflow and demonstrate its superiority in microbial detection and authentication, as well as substantially lower usage of computer memory.

Synthesis of Metabolites and Metabolite-like Compounds Using Biocatalytic Systems

Methodologies for the synthesis and purification of metabolites, which have been developed following their discovery, analysis, and structural identification, have been involved in numerous life science milestones. The renewed focus on the small molecule domain of biological cells has also created an increasing awareness of the rising gap between the metabolites identified and the metabolites which have been prepared as pure compounds. The design and engineering of resource-efficient and straightforward synthetic methodologies for the production of the diverse and numerous metabolites and metabolite-like compounds have attracted much interest. The variety of metabolic pathways in biological cells provides a wonderful blueprint for designing simplified and resource-efficient synthetic routes to desired metabolites. Therefore, biocatalytic systems have become key enabling tools for the synthesis of an increasing number of metabolites, which can then be utilized as standards, enzyme substrates, inhibitors, or other products, or for the discovery of novel biological functions.

Deep-time paleogenomics and the limits of DNA survival

Although most ancient DNA studies have focused on the last 50,000 years, paleogenomic approaches can now reach into the early Pleistocene, an epoch of repeated environmental changes that shaped present-day biodiversity. Emerging deep-time genomic transects, including from DNA preserved in sediments, will enable inference of adaptive evolution, discovery of unrecognized species, and exploration of how glaciations, volcanism, and paleomagnetic reversals shaped demography and community composition. In this Review, we explore the state-of-the-art in paleogenomics and discuss key challenges, including technical limitations, evolutionary divergence and associated biases, and the need for more precise dating of remains and sediments. We conclude that with improvements in laboratory and computational methods, the emerging field of deep-time paleogenomics will expand the range of questions addressable using ancient DNA.

Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning

Molecular de-extinction could offer avenues for drug discovery by reintroducing bioactive molecules that are no longer encoded by extant organisms. To prospect for antimicrobial peptides encrypted within extinct and extant human proteins, we introduce the panCleave random forest model for proteome-wide cleavage site prediction. Our model outperformed multiple protease-specific cleavage site classifiers for three modern human caspases, despite its pan-protease design. Antimicrobial activity was observed in vitro for modern and archaic protein fragments identified with panCleave. Lead peptides showed resistance to proteolysis and exhibited variable membrane permeabilization. Additionally, representative modern and archaic protein fragments showed anti-infective efficacy against A. baumannii in both a skin abscess infection model and a preclinical murine thigh infection model. These results suggest that machine-learning-based encrypted peptide prospection can identify stable, nontoxic peptide antibiotics. Moreover, we establish molecular de-extinction through paleoproteome mining as a framework for antibacterial drug discovery.