Davide Sassera

Bacterial endosymbionts are often unculturable, making sequencing-based approaches essential for their discovery and characterization. Here we developed SYMBIO-SCAN, a dedicated workflow for recovering high-quality nearly full-length 16S rRNA gene sequences of symbionts from long reads, which provided an adequate discriminatory power for identification and for accurate phylogenetic analyses. After validation on a mock community, we applied this workflow to 30 beetle (Coleoptera) specimens from 10 species. Beetles were selected since they host a wide variety of bacterial symbionts, able to influence host physiology, ecology, population dynamics, and evolution. Despite their importance, most of these symbionts remain completely unknown or poorly characterized. By the novel approach, we obtained 80 high-quality sequences belonging to diverse bacterial lineages, mostly Rickettsiales and Enterobacterales . Putative reproductive manipulators were among the most frequently detected symbionts, including Wolbachia , Rickettsia , “ Candidatus Lariskella”, Arsenophonus , and Spiroplasma . Moreover, three putative novel genera and one additional putative novel species were identified, including a possible Enterobacterales nutritional symbiont of the weevil Holotrichapion pisi . Overall, our results support that full-length 16S rRNA gene amplicon sequencing combined with tailored bioinformatic analyses provide a quick, cost-effective, and robust approach for investigating the diversity of host-associated bacterial symbionts, also allowing the discovery of entirely novel lineages.

Mosquitoes are vectors of numerous pathogens that pose significant threats to human and animal health, making their monitoring crucial for effective disease control. Environmental DNA (eDNA)–based approaches enable the detection of multiple organisms in their habitats without the need for morphological identification. However, they require strict and extensive protocol optimization. In this study, we focused on the need for novel monitoring strategies, particularly ones capable of overcoming the limitations of traditional methods. Given the central role of water in the life cycle of mosquitoes, we explored whether eDNA collected from aquatic habitats could provide an effective tool for mosquito detection and taxonomic identification. Specifically, we aimed to evaluate whether an eDNA‐based approach can reliably detect multiple mosquito species and accurately discriminate among them under different community compositions. To this end, we developed and validated a protocol for an eDNA‐based detection and identification method for mosquito monitoring. First, we assessed its performance by conducting laboratory experiments on samples containing nine different combinations of larvae from five mosquito species. eDNA occupancy analysis revealed varying species‐specific detection probabilities, with Aedes albopictus showing the highest detection rate and Aedes koreicus the lowest. Overall detection probability was high at moderate to high larval densities (5 to 50 ind/L), whereas it decreased at 0.5 ind/L, indicating reduced sensitivity at very low larval concentrations. Then, we collected 165 water samples from three types of field locations and assessed the influence of ecological variables, including land use and site type, on mosquito detection probability. Our results indicate that eDNA represents a promising tool for mosquito monitoring, particularly in contexts where larval densities are not extremely low, and may support its future integration into vector surveillance and control program.

Ticks (Ixodida) are the second most important vectors of infectious diseases in vertebrates, after mosquitoes. Beyond vector roles, they maintain mutualistic associations with bacteria, including endosymbionts that provide essential B vitamins lacking in their blood-based diet. The most extensively studied endosymbionts belong to the genera Coxiella, Midichloria, and Francisella. The genus Francisella encompasses endosymbionts (FE), pathogens (FP), opportunistic pathogens (FO) and free-living environmental strains (FL), making it a powerful system for evolutionary and comparative genomic analyses. In this study, total DNA from six adult female ticks of the genera Hyalomma and Amblyomma was sequenced to generate new FE genomes. Seven deeply sequenced public metagenomes were also assembled, yielding 69 Francisella, and as outgroup, three Allofrancisella, a Parafrancisella, and a Pseudofrancisella strains. This dataset supported phylogenomic reconstruction and comparison of genomic features, including vitamin biosynthesis and virulence pathways, with a focus on transitions to tick endosymbiosis. A densely sampled multi-locus sequence typing phylogeny was constructed to explore biogeographic patterns. Our results show that, except for FE, no ecological trait is monophyletic, supporting an origin of Francisella diversity from free-living ancestors. Biogeography suggests Palearctic and Afrotropical FE strains are derived and may involve horizontal transfers. Francisella comparative genomics reveals two contrasting profiles: environmental generalists and host-restricted specialists. These findings reinforce the role of tick FEs as nutritional mutualists, retaining key pathways such as riboflavin, shikimate, and biotin biosynthesis. In contrast, virulence is not ancestrally conserved but an innovation in pathogenic lineages, largely degraded in tick FEs. These results advance understanding of endosymbiont evolution and provide genomic insights with potential for disease control.

Cryptosporidium spp. are protozoan parasites responsible for diarrheal diseases. In humans, cryptosporidiosis is predominantly caused by the human-specific Cryptosporidium hominis and by Cryptosporidium parvum. This second species has been classically reported as zoonotic, with a host preference for ruminants. However, the recently described subspecies C. parvum anthroponosum has been found to be restricted to humans. Here, we generated novel whole genome sequences from West African samples of C. p. anthroponosum , and analyzed them together with all those already available, originating from East Africa, Europe, North America and Asia. Phylogenomics showed that all C. p. anthroponosum isolates are strongly clustered together, forming the sister clade of the zoonotic C. parvum representatives. The phylogenetic variations within C. p. anthroponosum did not present a clear geographic structure, consistent with C. hominis , primarily transmitted in humans. To elucidate the evolution of host species adaptation in C. p. anthroponosum , we then investigated genetic exchanges with C. hominis , detecting an ancestral introgression present in all C. p. anthroponosum isolates. This introgression involved a single gene, encoding for an extracellular galectin-like protein, which we predicted with high confidence to form a protein complex with the human insulin-degrading enzyme, a key metabolic regulator. Considering the role of host insulin metabolism in the proliferation of parasites as well as its known intrinsic differences between humans and ruminants, this molecular interaction could represent a plausible mechanism for an important role of the galectin-like protein in host-parasite interactions and in the host specificity of C. p. anthroponosum .

Yeasts belonging to the Candida genus typically reside on the mucosal surface and within the respiratory and gastrointestinal tract as commensals. Under conditions of host vulnerability, they can act as opportunistic pathogens, leading to various forms of candidiasis, including candidemia. Such infections can be particularly problematic when caused by isolates that exhibit resistance to antifungal drugs, which are becoming more prevalent in many regions. One hundred and seven samples of Candida spp. were isolated from patients with candidemia in the hospital San Matteo in Pavia (Italy) over a period of 6 years, from 2015 to the first COVID wave in spring 2020. In order to understand the epidemiology of Candida infections in this hospital setting, the isolates were whole-genome sequenced, confirming that most belonged to C. parapsilosis and C. albicans . Comparative genomics revealed that isolates of C. albicans were genomically diverse, indicative of repeated introductions in the hospital from the community. C. parapsilosis isolates on the other hand belonged to two groups of highly similar isolates, representing strains capable of long-term persistence in the hospital. All isolates of the main persistent group were resistant to fluconazoleresulting from the Y132F substitution in ERG11 and the N455D substitution in UPC2 , while presenting variable levels of resistance to voriconazole and itraconazole. Interestingly, with the exception of the single isolate susceptible to both voriconazole and itraconazole, all the 61 isolates presented one unreported missense mutation in MRR1 (S1907C).

Borrelia burgdorferi sensu lato bacteria are the causative agents of Lyme borreliosis, a multisystemic illness with an expanding epidemiology in temperate areas. Genomic studies on Borrelia are hindered by the difficulty of culturing procedures: standard protocols require extended incubation, substantial technical expertise, and are prone to failure, limiting timely recovery of isolates. This contributes to a low number of complete Borrelia genomes available in public repositories, particularly for species other than B. burgdorferi sensu stricto. Here we introduce a novel approach that overcomes the necessity for extended culture by utilizing Whole Genome Amplification (WGA) directly on freshly collected ticks, and that can be performed in parallel to classical culturing. The protocol is paired with a tailored bioinformatic pipeline designed to ensure accurate assembly and reliable downstream analyses. Benchmarking on multiple control isolates demonstrated that the method yields high-quality chromosomal assemblies. To demonstrate practical applicability, we applied the protocol to freshly collected ticks, successfully generating five high-quality Borrelia chromosomes (two B. lusitaniae , two B. afzelii and one B. garinii ). By generating sequencing-ready DNA in five days rather than months, our protocol greatly streamlines the process and minimizes the effort associated with traditional culture-based methods. This workflow will facilitate broader representation of understudied Borrelia species and support future epidemiological, ecological, and evolutionary investigations on this pathogen.

Pseudomonas aeruginosa is an important nosocomial pathogen which can cause serious infections across diverse anatomic locations. Infections can spread within an individual to different body sites, but the rate and directionality of this process is unknown. Here, we explore within-host diversity as well as the body site translocation dynamics using de-convoluted metagenomic P. aeruginosa reads from 256 hospital patients sampled at both respiratory and gut sites. Of the 84 patients where P. aeruginosa genomes could be recovered, there were 27 cases where the same P. aeruginosa clone was detected across multiple body sites. Using a simulation approach, we find that the majority of body site sharing is likely due to within-patient translocation of clones rather than independent acquisition from the hospital environment. Using ancestral reconstruction, we predict that most clones likely occupied a respiratory niche, and that the probable direction of clone transmission is lung-to-gut. Analysis of within-patient variation highlights strong enrichment of mutations in genes associated with antimicrobial resistance, irrespective of sample type. We report significantly more translocation than has been previously reported and highlight that lower respiratory tract infections can result in persistent gut colonisation of P. aeruginosa , a major risk factor for sepsis in vulnerable patients.

BACKGROUND: Ciprofloxacin resistant Klebsiella pneumoniae is common or emerging in many geographies, and knowledge of local resistance rates is important for empirical therapy. Whilst there are known K. pneumoniae ciprofloxacin resistance determinants, there is a lack of systematic data on the effect of determinants, alone and in combination, and there are no publicly accessible tools for predicting resistance from whole genome sequence data. METHODS: The KlebNET-GSP AMR Genotype-Phenotype Group aggregated a matched genotype-phenotype dataset of n=12,167 K. pneumoniae species complex ( Kp SC) isolates from 27 countries between 2001-2021. We developed a rules-based classifier to predict ciprofloxacin resistance by categorizing the number of quinolone resistance determining regions mutations in gyrA and parC , the number of plasmid-mediated quinolone resistance genes, and the presence/absence of aac(6ʹ)-Ib-cr (which can acetylate ciprofloxacin). Predictive performance was assessed using the discovery dataset, for which we re-phenotyped discrepant isolates; and validated using externally contributed datasets (n=7,030 Kp SC isolates). RESULTS: The rules-based classifier predicted R vs S/I with categorical agreement, sensitivity, and specificity >96%, and major/very major error rates Kp SC sources (human, animal, other), species, and intra-species lineages. External validation of the classifier yielded overall 93.12% categorical agreement [95% confidence interval (CI), 92.50-93.74%], 8.65% major errors [95% CI, 7.34-9.97%], and 6.20% very major errors [95% CI, 5.51-6.90%]. We implemented the classifier in Kleborate, a command-line tool that is integrated into the Pathogenwatch web platform. Using this to assess the global distribution of ciprofloxacin resistance determinants in Kp SC genomes available in Pathogenwatch (n=31,319, from 109 countries between years 2000-2023), we observed a significant positive association between national quinolone consumption rates and predicted ciprofloxacin resistance (R ² =0.20, p=0.004). CONCLUSIONS Ciprofloxacin resistance phenotypes can be reasonably predicted from genotypes, which is sufficient for informing surveillance. However, unexplained resistance remains and accuracy is insufficient for clinical applications. We demonstrate the value of aggregating genotype-phenotype data to explore resistance mechanisms and develop predictors, but highlight complexities in combining phenotype data from different assays and standards.

Genome plasticity can be defined as the capacity of a bacterial population to swiftly gain or lose genes. The time factor plays a fundamental role in the evolutionary success of microbes, particularly when considering pathogens and their tendency to gain antimicrobial resistance factors under the pressure of the extensive use of antibiotics. Multiple metrics have been proposed to provide insights into the gene content repertoire, yet they overlook the temporal component, which has a critical role in determining the adaptation and survival of a bacterial strain. In this study, we introduce a novel index that incorporates evolutionary distance to assess the rate at which bacteria exchange genes, thus fitting the definition of plasticity. Opposite to available indexes, our method also takes into account the possibility of contiguous genes being transferred together in one single event. We applied our novel index to measure plasticity in three widely studied bacterial species: Klebsiella pneumoniae, Staphylococcus aureus and Escherichia coli. Our results highlight distinctive plasticity patterns in specific sequence types and clusters, suggesting a possible correlation between heightened genome plasticity and globally recognized high-risk clones. Our approach holds promise as an index for predicting the emergence of strains of potential clinical concern, possibly allowing for timely and more effective interventions.

: Ticks (Ixodida) are the second most important vectors of infectious diseases in vertebrates, after mosquitoes. They also maintain mutualistic relationships with bacteria, such as endosymbionts that provide essential B vitamins absent in their blood diet. The most studied endosymbionts belong to the genera Coxiella , Midichloria , and Francisella . Francisella includes endosymbionts (FE), pathogens (FP), putative intermediates (FI), and free-living (FL) strains, making them valuable for evolutionary and comparative genomics. In this study, total DNA from six adult female ticks of the genera Hyalomma and Amblyomma was sequenced to obtain new FE genomes. Additionally, two deep metagenomes from public data were assembled, resulting in a dataset of 22 Francisella strains. This dataset was used to reconstruct a phylogenomic framework and compare vitamin biosynthesis and virulence pathways. An MLST-based dense phylogeny was also built to explore biogeographic patterns. The resulting phylogenomic tree shows FE form a monophyletic group derived from FP, possibly due to historical biogeography or recent horizontal transfers. Comparative analyses reveal that FE retain key metabolic pathways while losing nonessential ones, reflecting a selective genome reduction. These results advance our understanding of symbiont evolution in a changing world, revealing molecular adaptations that underpin tick- symbiont relationships and offering genomic insights with potential applications for disease control.