Guido completed an MSc in Veterinary Medicine at the University of Bologna in 2004. From there he was selected to attend a Specialisation School (equivalent to PGDip) on Animal Health, Breeding and Livestock Products that he completed with honours, submitting a thesis on The Use of Geographic Information Systems in Veterinary Medicine.
In 2007 Guido was awarded a DEFRA (FERA) PhD studentship in the Department of Virology at the University of Surrey, under the supervision of Prof Lisa Roberts and Dr Giles Budge. The project involved the Characterisation and Epidemiology of honey bee viruses in England and Wales.
Upon completing his PhD, Guido undertook successive fixed term Postdoctoral positions with Prof Roberto La Ragione working on molecular diagnostic of different animal bacterial and mycotic diseases and on comparative genomics of Escherichia coli (APEC-UPEC), Campylobacter and Clostridium perfringens.
From February 2016 to 2019, Guido worked in the University of York on the LANGELIN project 'Meeting Darwin's last challenge: toward a global tree of human languages and genes'.
From November 2019 he works as a Research Fellow in Molecular Microbiology, working on the One Health European Joint Programme, in the Department of Pathology and Infectious Diseases.
Areas of specialism
Affiliations and memberships
VMS2003 - FOUNDATIONS OF DISEASE THREE - PATHOLOGY OF THE INTEGUMENT AND ALIMENTARY SYSTEMS
Peritoneal & Retroperitoneal Pathology
Introduction: Accurate and rapid diagnostics paired with effective tracking and tracing systems are key to halting the spread of infectious diseases, limiting the emergence of new variants and to monitor vaccine efficacy. The current gold standard test (RT-qPCR) for COVID-19 is highly accurate and sensitive, but is time-consuming, and requires expensive specialised, lab-based equipment. Methods: Herein, we report on the development of a SARS-CoV-2 (COVID-19) rapid and inexpensive diagnostic platform that relies on a reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay and a portable smart diagnostic device. Automated image acquisition and an Artificial Intelligence (AI) deep learning model embedded in the Virus Hunter 6 (VH6) device allow to remove any subjectivity in the interpretation of results. The VH6 device is also linked to a smartphone companion application that registers patients for swab collection and manages the entire process, thus ensuring tests are traced and data securely stored. Results: Our designed AI-implemented diagnostic platform recognises the nucleocapsid protein gene of SARS-CoV-2 with high analytical sensitivity and specificity. A total of 752 NHS patient samples, 367 confirmed positives for coronavirus disease (COVID-19) and 385 negatives, were used for the development and validation of the test and the AI-assisted platform. The smart diagnostic platform was then used to test 150 positive clinical samples covering a dynamic range of clinically meaningful viral loads and 250 negative samples. When compared to RT-qPCR, our AI-assisted diagnostics platform was shown to be reliable, highly specific (100%) and sensitive (98–100% depending on viral load) with a limit of detection of 1.4 copies of RNA per µL in 30 min. Using this data, our CE-IVD and MHRA approved test and associated diagnostic platform has been approved for medical use in the United Kingdom under the UK Health Security Agency’s Medical Devices (Coronavirus Test Device Approvals, CTDA) Regulations 2022. Laboratory and in-silico data presented here also indicates that the VIDIIA diagnostic platform is able to detect the main variants of concern in the United Kingdom (September 2023). Discussion: This system could provide an efficient, time and cost-effective platform to diagnose SARS-CoV-2 and other infectious diseases in resource-limited settings.
Historical explanations in science are primarily concerned with the reconstruction of initial conditions determining observable later events. Historical linguistics focuses on the reconstruction of at least two different types of initial conditions: protolanguages and phylogenetic relationships. The fundamental tool for reconstructing phylogenetic relationships is language comparison. To date, the classical historical‐comparative method qualifies as the most significant contribution to historical reconstruction in linguistics. This chapter reviews the design, tenets, and results of the parametric comparison method. Parametric models presuppose that the human language faculty is characterized by a certain amount of species‐invariant knowledge, and encode grammatical diversity in the form of binary values that define the availability of various morphosyntactic properties for each language. The chapter summarizes the main distinctive properties attributed to syntactic parameters and shows that parametric distances do not saturate even when moved toward the discrimination of close dialectal varieties.
To reconstruct aspects of human demographic history, linguistics and genetics complement each other, reciprocally suggesting testable hypotheses on population relationships and interactions. Relying on a linguistic comparative method based on syntactic data, here we focus on the non-straightforward relation of genes and languages among Finno-Ugric (FU) speakers, in comparison to their Indo-European (IE) and Altaic (AL) neighbors. Syntactic analysis, in agreement with the indications of more traditional linguistic levels, supports at least three distinct clusters, corresponding to these three Eurasian families; yet, the outliers of the FU group show linguistic convergence with their geographical neighbors. By analyzing genome-wide data in both ancient and contemporary populations, we uncovered remarkably matching patterns, with north-western FU speakers linguistically and genetically closer in parallel degrees to their IE-speaking neighbors, and eastern FU speakers to AL speakers. Therefore, our analysis indicates that plausible cross-family linguistic interference effects were accompanied, and possibly caused, by recognizable demographic processes. In particular, based on the comparison of modern and ancient genomes, our study identified the Pontic-Caspian steppes as the possible origin of the demographic processes that led to the expansion of FU languages into Europe.
Background Avian pathogenic Escherichia coli (APEC) causes colibacillosis, which results in significant economic losses to the poultry industry worldwide. However, the diversity between isolates remains poorly understood. Here, a total of 272 APEC isolates collected from the United Kingdom (UK), Italy and Germany were characterised using multiplex polymerase chain reactions (PCRs) targeting 22 equally weighted factors covering virulence genes, R-type and phylogroup. Following these analysis, 95 of the selected strains were further analysed using Whole Genome Sequencing (WGS). Results The most prevalent phylogroups were B2 (47%) and A1 (22%), although there were national differences with Germany presenting group B2 (35.3%), Italy presenting group A1 (53.3%) and UK presenting group B2 (56.1%) as the most prevalent. R-type R1 was the most frequent type (55%) among APEC, but multiple R-types were also frequent (26.8%). Following compilation of all the PCR data which covered a total of 15 virulence genes, it was possible to build a similarity tree using each PCR result unweighted to produce 9 distinct groups. The average number of virulence genes was 6-8 per isolate, but no positive association was found between phylogroup and number or type of virulence genes. A total of 95 isolates representing each of these 9 groupings were genome sequenced and analysed for in silico serotype, Multilocus Sequence Typing (MLST), and antimicrobial resistance (AMR). The UK isolates showed the greatest variability in terms of serotype and MLST compared with German and Italian isolates, whereas the lowest prevalence of AMR was found for German isolates. Similarity trees were compiled using sequencing data and notably single nucleotide polymorphism data generated ten distinct geno-groups. The frequency of geno-groups across Europe comprised 26.3% belonging to Group 8 representing serogroups O2, O4, O18 and MLST types ST95, ST140, ST141, ST428, ST1618 and others, 18.9% belonging to Group 1 (serogroups O78 and MLST types ST23, ST2230), 15.8% belonging to Group 10 (serogroups O8, O45, O91, O125ab and variable MLST types), 14.7% belonging to Group 7 (serogroups O4, O24, O35, O53, O161 and MLST type ST117) and 13.7% belonging to Group 9 (serogroups O1, O16, O181 and others and MLST 51 types ST10, ST48 and others). The other groups (2, 3, 4, 5 and 6) each contained relatively few strains. However, for some of the genogroups (e.g. groups 6 and 7) partial overlap with SNPs grouping and PCR grouping (matching PCR groups 8 (13 isolates on 22) and 1 (14 isolates on 16) were observable). However, it was not possible to obtain a clear correlation between genogroups and unweighted PCR groupings. This may be due to the genome plasticity of E. coli that enables strains to carry the same virulence factors even if the overall genotype is substantially different. Conclusions The conclusion to be drawn from the lack of correlations is that firstly, APEC are very diverse and secondly, it is not possible to rely on any one or more basic molecular or phenotypic tests to define APEC with clarity, reaffirming the need for whole genome analysis approaches which we describe here. This study highlights the presence of previously unreported serotypes and MLSTs for APEC in Europe. Moreover, it is a first step on a cautious reconsideration of the merits of classical identification criteria such as R typing, phylogrouping and serotyping.
This study assessed the prevalence and zoonotic potential of Shiga toxin-producing Escherichia coli (STEC) sampled from 104 dairy units in the central region of Zambia and compared these with isolates from patients presenting with diarrhoea in the same region. A subset of 297 E. coli strains were sequenced allowing in silico analyses of phylo- and sero-groups. The majority of the bovine strains clustered in the B1 ‘commensal’ phylogroup (67%) and included a diverse array of serogroups. 11% (41/371) of the isolates from Zambian dairy cattle contained Shiga toxin genes (stx) while none (0/73) of the human isolates were positive. While the toxicity of a subset of these isolates was demonstrated, none of the randomly selected STEC belonged to key serogroups associated with human disease and none encoded a type 3 secretion system synonymous with typical enterohaemorrhagic strains. Positive selection for E. coli O157:H7 across the farms identified only one positive isolate again indicating this serotype is rare in these animals. In summary, while Stx-encoding E. coli strains are common in this dairy population, the majority of these strains are unlikely to cause disease in humans. However, the threat remains of the emergence of strains virulent to humans from this reservoir.
Pigs infected with Salmonella may excrete large amounts of Salmonella, increasing the risk of spread of this pathogen in the food chain. Identifying Salmonella high shedder pigs is therefore required to mitigate this risk. We analyzed immune-associated markers and composition of the gut microbiota in specific-pathogen-free pigs presenting different shedding levels after an oral infection with Salmonella. Immune response was studied through total blood cell counts, production of anti-Salmonella antibodies and cytokines, and gene expression quantification. Total Salmonella shedding for each pig was estimated and hierarchical clustering was used to cluster pigs into high, intermediate, and low shedders. Gut microbiota compositions were assessed using 16S rRNA microbial community profiling. Comparisons were made between control and inoculated pigs, then between high and low shedders pigs. Prior to infection, high shedders had similar immunological profiles compared to low shedders. As soon as 1 day postinoculation (dpi), significant differences on the cytokine production level and on the expression level of several host genes related to a proinflammatory response were observed between high and low shedders. Infection with Salmonella induced an early and profound remodeling of the immune response in all pigs, but the intensity of the response was stronger in high shedders. In contrast, low shedders seroconverted earlier than high shedders. Just after induction of the proinflammatory response (at 2 dpi), some taxa of the fecal microbiota were specific to the shedding phenotypes. This was related to the enrichment of several functional pathways related to anaerobic respiration in high shedders. In conclusion, our data show that the immune response to Salmonella modifies the fecal microbiota and subsequently could be responsible for shedding phenotypes. Influencing the gut microbiota and reducing intestinal inflammation could be a strategy for preventing Salmonella high shedding in livestock. Salmonellosis remains the most frequent human foodborne zoonosis after campylobacteriosis and pork meat is considered one of the major sources of human foodborne infections. At the farm, host heterogeneity in pig infection is problematic. High Salmonella shedders contribute more significantly to the spread of this foodborne pathogen in the food chain. The identification of predictive biomarkers for high shedders could help to control Salmonella in pigs. The purpose of the present study was to investigate why some pigs become super shedders and others low shedders. We thus investigated the differences in the fecal microbial composition and the immune response in orally infected pigs presenting different Salmonella shedding patterns. Our data show that the proinflammatory response induced by Typhimurium at 1 dpi could be responsible for the modification of the fecal microbiota composition and functions observed mainly at 2 and 3 dpi and to the low and super shedder phenotypes.