Biology subjects

Cardoso, M. J.

Publications and source records attributed to Cardoso, M. J..

5 recordsLinked to original sources

bioRxiv2024

Enhancing antimicrobial resistance monitoring: Core Plasmid Multi-Locus sequence typing (cpMLST) with Oxford Nanopore sequencing technology (ONT)

BackgroundThe spread of antimicrobial resistance (AMR) poses a significant threat to global public health, primarily driven by the horizontal gene transfer of resistance genes via plasmids. Understanding the dynamics of plasmid transmission within (intra) and between (inter) bacterial species is crucial for developing effective countermeasures. In this study, we utilize long-read sequencing technology to develop an innovative approach called core plasmid Multi-Locus Sequence Typing (cpMLST) and track the global plasmid transmission pathways. MethodsWe collected wastewater samples from six different hospitals in Germany. Within 24 hours of collection, we isolated extensively drug-resistant (XDR) bacteria using CHROMagar plates (CHROMagar, Paris, France). Species identification was done using MALDI-TOF MS (Bruker Daltonics, Bremen, Germany). Genomic DNA from the isolates was extracted using the PureLink Genomic DNA Mini Kit (Invitrogen, Carlsbad, USA) and subsequently sequenced using Oxford Nanopore Technologies (ONT) sequencing (Oxford Nanopore Technologies). We employed the SQK-RBK114.24 kit on an R10.4.1 flow cell, achieving a minimum of 250 Mb of raw data for each isolate with an accuracy of 98.9%. The reads were assembled using Unicycler, and the quality of the assemblies was assessed using QUAST and Bandage. The assembled genomes were then uploaded to the Center for Genomic Epidemiology (CGE) https://www.genomicepidemiology.org/ platform to determine incompatibility (Inc) types and antimicrobial resistance (AMR) genes. Additionally, we performed core plasmid analysis using chewBBACA v.3.3.10 to assess plasmid relatedness. ResultsThe analysis confirmed the identification of various bacterial isolates. Among the most prevalent XDR isolate were Enterobacter roggenkampii (n=38), Serratia marcescens (n=12), Klebseilla oxytoca (n=11), Klebseilla michiganensis (n=8), and Citrobacter freundii (n=7). We conducted a cpMLST analysis to examine the highly prevalent plasmids and reveal evolutionary relationships and transmission patterns. Each isolate harbored different types of complete plasmids. Among those were the IncFII (n=45), IncHI (n=26), IncX3 (n=21), and other incompatibility groups. By focusing on shared Inc types among the bacterial species, their transfer within a single bacterial species (intra-species transfer) and between different species (inter-species transfer) were identified. The allelic differences ranged from 3-55 (IncHI), 2-32 (IncFII) and 2-24 (IncX3). Moreover, these plasmids, typically identified as smaller plasmids (IncX3), were larger than their commonly reported sizes. The analysis of plasmid dynamics across diverse bacterial hosts provides valuable insight into the mechanisms driving the spread of antimicrobial resistance, offering potential strategies for better controlling the dissemination of antimicrobial resistance and its transmission in clinical environments. ConclusionIn conclusion, long-read sequencing technologies emerge as an essential tool for investigating the transmission dynamics of antimicrobial resistance genes among plasmids. By implementing cp-MLST, we anticipate achieving an unparalleled understanding of the global dissemination and evolutionary patterns of resistance-carrying plasmids. This approach offers superior resolution to conventional plasmid typing methods, potentially opening new avenues for innovative strategies to combat the escalating AMR crisis.

microbiology↗

bioRxiv2024

Zebrafish Avatar-test predicts patient's tumor response to chemotherapy in breast cancer: a co-clinical study towards personalized medicine

Chemotherapy remains the mainstay in most high-risk breast cancer (BC) settings, with several equivalent options of treatment. However, the efficacy of each treatment varies between patients and there is currently no test to determine which option will be the most effective for each individual patient. Here, we developed a fast in-vivo test for BC therapy screening: the zebrafish patient derived xenograft model (zAvatars), where in-vivo results can be obtained in just 10 days. To determine the predictive value of the BC zAvatars we performed a clinical study, where zAvatars were treated with the same therapy as the donor-patient and their response to therapy was compared. Our data shows a 100% correlation between patients clinical response to treatment and its matching zAvatar. Altogether, our results suggest that the zAvatar model constitutes a promising in-vivo assay to optimize cancer treatments in truly personalized manner.

cancer biology↗

bioRxiv2018

Application of mechanistic methods to clinical trials in multiple sclerosis: the simvastatin case

The analysis of clinical trials is limited to pre-specified outcomes, thereby precluding a mechanistic understanding of the treatment response. Multivariate mechanistic models can elucidate the causal chain of events by simultaneous analysis of multimodal data that link intermediate variables to outcomes of interest. A double-blind, randomised, controlled, phase 2 clinical trial in secondary progressive multiple sclerosis (MS-STAT, NCT00647348) demonstrated that simvastatin (80mg/day) over two years reduced the brain atrophy rate and was associated with beneficial effects on cognitive and disability outcomes. Therefore, this trial offers an opportunity to apply mechanistic models to investigate the hypothesised pathways that link simvastatin to clinical outcome measures, either directly or indirectly via changes in serum total cholesterol levels and to determine which is the more likely.

neuroscience↗

bioRxiv2017

Progression of regional grey matter atrophy in multiple sclerosis

Grey matter atrophy is present from the earliest clinical stages of multiple sclerosis (MS), but the temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in MS, and its association with disability accumulation.\n\nIn this longitudinal study, we included 1,417 subjects: 253 with clinically-isolated syndrome (CIS), 708 relapsing-remitting MS (RRMS), 128 secondary-progressive MS (SPMS), 125 primary-progressive MS (PPMS), and 203 healthy controls from 7 European centres. Subjects underwent repeated MRI scanning (total number of scans 3,604); the mean follow-up for patients was 2.41yrs (SD{+/-}1.97). Disability was scored using the Expanded Disability Status Scale (EDSS). We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template. We used an established data-driven event-based model (EBM) to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific EBM stage, based on the number of their atrophic regions. We used nested linear mixed-effects regression models to explore the associations between the rate of increase in the EBM stages over time, disease duration and annual rate of EDSS gain.\n\nThe first regions to become atrophic in CIS and relapse-onset MS patients (RRMS and SPMS) were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. The sequence of atrophy in PPMS showed a similar involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset MS and late atrophy in PPMS. Patients with SPMS showed the highest EBM stages (highest number of atrophic regions, all p<0.001) at study entry. Rates of increase in EBM stages were significantly different from healthy controls in all MS phenotypes, except for CIS. The increase in the number of atrophic regions (EBM stage) was associated with disease duration in all patients. EBM stage was associated with disability accumulation in RRMS independent of disease duration (p<0.0001).\n\nThis data-driven staging of atrophy progression in a large MS sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across MS phenotypes. The spread of atrophy was associated with disease duration, and disability accumulation in RRMS.\n\nAbbreviations

neuroscience↗

bioRxiv2017

Deep grey matter volume loss drives disability worsening in multiple sclerosis

ObjectiveGrey matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS.\n\nMethodsWe analysed 3,604 brain high-resolution T1-weighted MRI scans from 1,417 participants: 1,214 MS patients (253 clinically-isolated syndrome[CIS], 708 relapsingremitting[RRMS], 128 secondary-progressive[SPMS], 125 primary-progressive[PPMS]), over an average follow-up of 2.41 years (standard deviation[SD]=1.97), and 203 healthy controls (HCs) [average follow-up=1.83 year, SD=1.77], attending 7 European centres. Disability was assessed with the Expanded-Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem and cerebral white matter. Hierarchical mixed-models assessed annual percentage rate of regional tissue loss and identified regional volumes associated with time-to-EDSS progression.\n\nResultsSPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time-to-EDSS progression (hazard ratio=0.73, 95% CIs 0.65, 0.82; p<0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow-up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (-1.45%), PPMS (-1.66%), and RRMS (-1.34%) than CIS (-0.88%) and HCs (-0.94%)[p<0.01]. The rate of temporal GM atrophy in SPMS (-1.21%) was significantly faster than RRMS (-0.76%), CIS (-0.75%), and HCs (-0.51%). Similarly, the rate of parietal GM atrophy in SPMS (-1.24-%) was faster than CIS (-0.63%) and HCs (-0.23%) (all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta=0.04, p<0.001).\n\nInterpretationThis large multi-centre and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions.

neuroscience↗