Exploring the potential of Physics-Informed Neural Networks to extract vascularization data from DCE-MRI in the presence of diffusion.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used to assess tissue vascularization, particularly in oncological applications. However, the most widely used pharmacokinetic (PK) models do not account for contrast agent (CA) diffusion between neighboring voxels, which can limit the accuracy of the results, especially in cases of heterogeneous tumors. To address this issue, previous works have proposed algorithms that incorporate diffusion phenomena into the formulation. However, these algorithms often face convergence problems due to the ill-posed nature of the problem. In this work, we present a new approach to fitting DCE-MRI data that incorporates CA diffusion by using Physics-Informed Neural Networks (PINNs). PINNs can be trained to fit measured data obtained from DCE-MRI while ensuring the mass conservation equation from the PK model. We compare the performance of PINNs to previous algorithms on different 1D cases inspired by previous works from literature. Results show that PINNs retrieve vascularization parameters more accurately from diffusion-corrected tracer-kinetic models. Furthermore, we demonstrate the robustness of PINNs compared to other traditional algorithms when faced with noisy or incomplete data. Overall, our results suggest that PINNs can be a valuable tool for improving the accuracy of DCE-MRI data analysis, particularly in cases where CA diffusion plays a significant role.

A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma.

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumours, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. In this work we have developed this multi-scale model that includes data such as patient's tumour geometry, cellularity, vascularization, genetics and type of chemotherapy treatment, and integrated it into an online platform that runs the simulations on a high-performance computation cluster using Onedata and Kubernetes technologies. This infrastructure will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This manuscript outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development.

PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers.

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours.

A multimodal intervention program to control a long-term Acinetobacter baumannii endemic in a tertiary care hospital.

Background: Acinetobacter baumannii causes frequently nosocomial infections worldwide. Its ability to survive on dry surfaces facilitates its spread and the persistence of endemic situations, especially in the intensive care units (ICUs).The objective of this paper is to describe a multicomponent intervention program designed to control a hyperendemic persistence of multidrug-resistant A. baumannii (MDR-Ab) and to characterize its impact. Methods: Design: Quasi-experimental intervention study based on open cohorts.Setting: Public tertiary referral centre. Period: January 2009-August 2017.Intervention: multifaceted program based on environmental decontamination, hand hygiene, antimicrobial stewardship, contact precautions, active surveillance, weekly reports and regular meetings.Analysis: joinpoint regression and interrupted time-series analysis. Results: The intervention was successfully implemented. Through the study period, the compliance with contact precautions changed from 0 to 100% and with hand hygiene, from 41.8 to 82.3%. Between 2012 and 2016, the antibiotic consumption decreased from 165.35 in to 150.44 daily-defined doses/1000 patients-days in the ICU. The incidence density of MDR-Ab in the ICU was 10.9 cases/1000 patients-days at the beginning of the intervention. After this moment, the evolution of the incidence density of MDR-Ab was: between months 0 and 6°, it remained stable; between months 7° and 10°: there was an intense decrease, with an average monthly percentage change (AMPC) = - 30.05%; from 11° month until the end, the decrease was lighter but continuous (AMPC:-2.77%), achieving an incidence density of 0 cases/1000 patients-days on the 18° month, without any new case for 12 months. From the 30° month until the end of the study period, several little outbreaks of MDR-Ab were detected, all of them rapidly controlled. The strains of MDR-Ab isolated during these outbreaks were not clonally related with the previously endemic one, which supports its eradication from the environmental reservoirs. Conclusion: The multicomponent intervention performed by a multidisciplinary team was effective to eradicate the endemic MDR-Ab.

An iterative finite element-based method for solving inverse problems in traction force microscopy.

BACKGROUND AND OBJECTIVE: During the last years different model solutions were proposed for solving cell forces under different conditions. The solution relies on a deformation field that is obtained under cell relaxation with a chemical cocktail. Once the deformation field of the matrix is determined, cell forces can be computed by an inverse algorithm, given the mechanical properties of the matrix. Most of the Traction Force Microscopy (TFM) methods presented so far relied on a linear stress-strain response of the matrix. However, the mechanical response of some biopolymer networks, such as collagen gels is more complex. In this work, we present a numerical method for solving cell forces on non-linear materials. METHODS: The proposed method relies on solving the inverse problem based on an iterative optimization. The objective function is defined by least-square minimization of the difference between the target and the current computed deformed configuration of the cell, and the iterative formulation is based on the solution of several direct mechanical problems. The model presents a well-posed discretized inverse elasticity problem in the absence of regularization. The algorithm can be easily implemented in any kind of Finite Element (FE) code as a sequence of different standard FE analysis. RESULTS: To illustrate the proposed iterative formulation we apply the theoretical model to some illustrative examples by using real experimental data of Normal Human Dermal Fibroblast cells (NHDF) migrating inside a 2 mg/ml collagen-based gel. Different examples of application have been simulated to test the inverse numerical model proposed and to investigate the effect of introducing the correct cell properties onto the obtained cell forces. The algorithm converges after a small number of iterations, generating errors of around 5% for the tractions field in the cell contour domain. The resulting maximum traction values increased by 11% as a consequence of doubling the mechanical properties of the cell domain. CONCLUSIONS: With the results generated from computations we demonstrate the application of the algorithm and explain how the mechanical properties of both, the cell and the gel, domains are important for arriving to the correct results when using inverse traction force reconstruction algorithms, however, have only a minor effect on the resulting traction values.

In vitro study of synergy of ampicillin with ceftriaxone against Listeria monocytogenes.

OBJECTIVE: To evaluate if the in vitro activity of ampicillin increases when combined with ceftriaxone. METHODS: The activity of ampicillin and ceftriaxone was evaluated against six Listeria monocytogenes invasive clinical isolates. Ampicillin and ceftriaxone MICs were determined by the broth microdilution method. Synergy was evaluated by checkerboard and time-kill curves methods. RESULTS: All six L. monocytogenes strains were susceptible to ampicillin (MICs 0.25-0.5 mg/L). A bacteriostatic synergy was demonstrated by the FIC index of 0.5 and a 2.5 log10 CFU reduction on the six strains studied for MIC ampicillin plus 16 mg/L ceftriaxone concentrations. CONCLUSIONS: The association of ceftriaxone with ampicillin increases the in vitro activity of ampicillin, and therefore could be a valuable option in the treatment of invasive infection by L. monocytogenes.

Modelling actin polymerization: the effect on confined cell migration.

The aim of this work is to model cell motility under conditions of mechanical confinement. This cell migration mode may occur in extravasation of tumour and neutrophil-like cells. Cell migration is the result of the complex action of different forces exerted by the interplay between myosin contractility forces and actin processes. Here, we propose and implement a finite element model of the confined migration of a single cell. In this model, we consider the effects of actin and myosin in cell motility. Both filament and globular actin are modelled. We model the cell considering cytoplasm and nucleus with different mechanical properties. The migration speed in the simulation is around 0.1 µm/min, which is in agreement with existing literature. From our simulation, we observe that the nucleus size has an important role in cell migration inside the channel. In the simulation the cell moves further when the nucleus is smaller. However, this speed is less sensitive to nucleus stiffness. The results show that the cell displacement is lower when the nucleus is stiffer. The degree of adhesion between the channel walls and the cell is also very important in confined migration. We observe an increment of cell velocity when the friction coefficient is higher.

Monitoring the antimicrobial susceptibility of Gram-negative organisms involved in intraabdominal and urinary tract infections recovered during the SMART study (Spain, 2016 and 2017).

OBJECTIVE: Continuous antimicrobial resistance surveillance is recommended by Public Health authorities. We up-dated data from the SMART (Study for Monitoring Antimicrobial Resistance Trends) surveillance study in Spain. METHODS: The antimicrobial susceptibility data and extended-spectrum beta-lactamase (ESBL) production in isolates recovered from intra-abdominal (IAI) (n=1,429) and urinary tract (UTI) (n=937) infections during the 2016- 2017 SMART study in 10 Spanish hospitals were analysed. RESULTS: Escherichia coli was the most frequently microorganism isolated (48.3% and 53.7%) followed by Klebsiella spp. (11.5% and 21.9%) in IAIs and UTIs, respectively. Figures for Pseudomonas aeruginosa were 9.0% and 6.1%, being more frequently recovered from patients with nosocomial infections. Overall, 9.9% (IAI) and 14.0% (UTI) of E. coli, Klebsiella spp. and Proteus mirabilis isolates were ESBL-producers, being Klebsiella pneumoniae (34.5%) from UTI of nosocomial origin the most frequent. ESBL-producers were higher in patients >60 years in both IAIs and UTIs. As in previous years, amikacin (96.3%-100% susceptibility), ertapenem (84.2%-100%) and imipenem (70.3%- 100%) were the most active antimicrobials tested among Enterobacterales species. The activity of amoxicillin-clavulanic, piperacillin-tazobactam, and ciprofloxacin susceptibility was lower, particularly among ESBL-producers. Ertapenem susceptibility (88.9%-100%) was retained in ESBL-E. coli isolates that were resistant to these antimicrobials but decreased (28.6%-100%) in similar isolates of K. pneumoniae. CONCLUSIONS: Continuous antimicrobial resistance surveillance from the SMART study reveals overall maintenance of ESBL-producers in Spain, although with higher presence in isolates from UTIs than from IAIs. Moreover, ertapenem activity was high in E. coli irrespective of ESBL production but decreased in K. pneumoniae, particularly among ESBL-producers.

Linfoma tipo Burkitt con afectación ovárica como única manifestación inicial: caso clínico y revisión de la literatura / Ovarian Burkitt lymphoma as the primary manifestation: a case report and literature review

La afectación ovárica como debut de un linfoma de Burkitt sin enfermedad extraovárica detectable es anecdótica, por lo que habitualmente no se incluye como hipótesis diagnóstica tras el hallazgo de una tumoración ovárica. Su desconocimiento lleva a realizar un tratamiento equivocado que puede llegar a comprometer el deseo reproductivo de la paciente. Presentamos el caso de una paciente que presenta un linfoma de Burkitt con afectación ovárica como manifestación inicial. La paciente desarrolló una progresión sistemática excepcionalmente rápida. A propósito de este caso y de su inusual evolución, revisamos la literatura existente.

Ovarian involvement as the initial manifestation of a Burkitt lymphoma without detectable extra-ovarian disease is rare, which is why it is usually not included in the differential diagnosis when an ovarian tumor is detected. A missed diagnosis will lead to the wrong treatment being given, and this can compromise any future reproductive wishes of the patient. In this article, a patient presents a Burkitt lymphoma with ovarian involvement as an initial manifestation and an unusually rapid systemic progression of the disease. Prompted by this case and its unusual course, we reviewed the existing literature.

From individual to collective 3D cancer dissemination: roles of collagen concentration and TGF-ß.

Cancer cells have the ability to migrate from the primary (original) site to other places in the body. The extracellular matrix affects cancer cell migratory capacity and has been correlated with tissue-specific spreading patterns. However, how the matrix orchestrates these behaviors remains unclear. Here, we investigated how both higher collagen concentrations and TGF-ß regulate the formation of H1299 cell (a non-small cell lung cancer cell line) spheroids within 3D collagen-based matrices and promote cancer cell invasive capacity. We show that at low collagen concentrations, tumor cells move individually and have moderate invasive capacity, whereas when the collagen concentration is increased, the formation of cell clusters is promoted. In addition, when the concentration of TGF-ß in the microenvironment is lower, most of the clusters are aggregates of cancer cells with a spheroid-like morphology and poor migratory capacity. In contrast, higher concentrations of TGF-ß induced the formation of clusters with a notably higher invasive capacity, resulting in clear strand-like collective cell migration. Our results show that the concentration of the extracellular matrix is a key regulator of the formation of tumor clusters that affects their development and growth. In addition, chemical factors create a microenvironment that promotes the transformation of idle tumor clusters into very active, invasive tumor structures. These results collectively demonstrate the relevant regulatory role of the mechano-chemical microenvironment in leading the preferential metastasis of tumor cells to specific tissues with high collagen concentrations and TFG-ß activity.

A web-based application for automated quantification of chemical gradients induced in microfluidic devices.

Advances in microfabrication have allowed the development and popularization of microfluidic devices, which are powerful tools to recreate three-dimensional (3-D) biologically relevant in vitro models. These microenvironments are usually generated by using hydrogels and induced chemical gradients. Going further, computational models enable, after validation, the simulation of such conditions without the necessity of real experiments, thus saving costs and time. In this work we present a web-based application that allows, based on a previous numerical model, the assessment of different chemical gradients induced within a 3-D extracellular matrix. This application enables the estimation of the spatio-temporal chemical distribution inside microfluidic devices, by defining a first set of parameters characterizing the chip geometry, and a second set characterizing the diffusion properties of the hydrogel-based matrix. The simulated chemical concentration profiles generated within a synthetic hydrogel are calculated remotely on a server and returned to the website in less than 3 min, thus offering a quick automatic quantification to any user. To ensure the day-to-day applicability, user requirements were investigated prior to tool development, pre-selecting some of the most common geometries. The tool is freely available online, after user registration, on http://m2be.unizar.es/insilico_cell under the software tab. Four different microfluidic device geometries were defined to study the dependence of the geometrical parameters onto the gradient formation processes. The numerical predictions demonstrate that growth factor diffusion within 3-D matrices strongly depends not only on the physics of diffusion, but also on the geometrical parameters that characterizes these complex devices. Additionally, the effect of the combination of different hydrogels inside a microfluidic device was studied. The automatization of microfluidic device geometries generation provide a powerful tool which facilitates to any user the possibility to automatically create its own microfluidic device, greatly reducing the experimental validation processes and advancing in the understanding of in vitro 3-D cell responses without the necessity of using commercial software or performing real testing experiments.

Antimicrobial susceptibility trends and evolution of isolates with extended spectrum ß-lactamases among Gram-negative organisms recovered during the SMART study in Spain (2011-2015).

OBJECTIVE: The SMART (Study for Monitoring Antimicrobial Resistance Trends) surveillance study monitors antimicrobial susceptibility and extended spectrum ß-lactamases (ESBLs) in Gram-negative bacilli recovered from intra-abdominal infections (IAI). METHODS: Antimicrobial susceptibility of 5,343 isolates from IAI recovered in 11 centres during the 2011-2015 SMART-Spain program was analysed by standard microdilution (EUCAST criteria) and compared with that from 2002-2010. ESBLs were phenotypically detected. RESULTS: Escherichia coli, the most common isolate, significantly decreased in community acquired IAI (60.9% 2002-2010 vs. 56.1% 2011-2015, P=0.0003). It was followed in prevalence by Klebsiella pneumoniae that increased both in the community (8.9% vs. 10.8%, P=0.016) and nosocomial (9.2% vs. 10.8%, P=0.029) IAI and P. aeruginosa, which significantly increased in community acquired IAI (5.6% vs. 8.0%, P=0.0003). ESBLs were more prevalent in K. pneumoniae (16.3%) than in E. coli (9.5%) of nosocomial origin and were more frequently isolated from elderly patients (>60 years). Considering all Enterobacteriaceae, ertapenem (92.3-100%) and amikacin (95.5%-100%) were the most active antimicrobials. Ertapenem activity, unlike amoxicillin-clavulanate or piperacillin-tazobactam, remained virtually unchanged in ESBL (100%) and non-ESBL (98.8%) E. coli producers. Its activity decreased in ESBL-K. pneumoniae (74.7%) but was higher than that of amoxicillin-clavulanate (14.0%) and piperacillin-tazobactam (24.0%). Interestingly, ertapenem susceptibility was maintained in >60% of ESBL isolates that were resistant to amoxicillin-clavulanate, piperacillin-tazobactam or fluoroquinolones. CONCLUSIONS: SMART-Spain results support current guidelines which include ertapenem as empiric treatment in mild-moderate community-acquired IAI, particularly with ESBL producers. These recommendations will need to be updated with the recently introduction of new antimicrobials.

Degradation of extracellular matrix regulates osteoblast migration: A microfluidic-based study.

Bone regeneration is strongly dependent on the capacity of cells to move in a 3D microenvironment, where a large cascade of signals is activated. To improve the understanding of this complex process and to advance in the knowledge of the role of each specific signal, it is fundamental to analyze the impact of each factor independently. Microfluidic-based cell culture is an appropriate technology to achieve this objective, because it allows recreating realistic 3D local microenvironments by taking into account the extracellular matrix, cells and chemical gradients in an independent or combined scenario. The main aim of this work is to analyze the impact of extracellular matrix properties and growth factor gradients on 3D osteoblast movement, as well as the role of cell matrix degradation. For that, we used collagen-based hydrogels, with and without crosslinkers, under different chemical gradients, and eventually inhibiting metalloproteinases to tweak matrix degradation. We found that osteoblast's 3D migratory patterns were affected by the hydrogel properties and the PDGF-BB gradient, although the strongest regulatory factor was determined by the ability of cells to remodel the matrix.

Urinary Tract Conditions Affect Fosfomycin Activity against Escherichia coli Strains Harboring Chromosomal Mutations Involved in Fosfomycin Uptake.

The steps by which Escherichia coli strains harboring mutations related to fosfomycin (FOS) resistance arise and spread during urinary tract infections (UTIs) are far from being understood. The aim of this study was to evaluate the effects of urine, pH, and anaerobiosis on FOS activity against a set of isogenic strains carrying the most prevalent chromosomal mutations conferring FOS resistance (ΔuhpT, ΔglpT, ΔcyaA, and ΔptsI), either singly or in combination. We also studied fosfomycin-resistant E. coli clinical isolates from patients with UTI. Our results demonstrate that urinary tract physiological conditions might have a profound impact on FOS activity against strains with chromosomal FOS resistance mutations. Specifically, acidic pH values and anaerobiosis convert most of the strains categorized as resistant to fosfomycin according to the international guidelines to a susceptible status. Therefore, urinary pH values may have practical interest in the management of UTIs. Finally, our results, together with the high fitness cost associated with FOS resistance mutations, might explain the low prevalence of fosfomycin-resistant E. coli variants in UTIs.

Traction Force Microscopy in 3-Dimensional Extracellular Matrix Networks.

Cell migration through a three-dimensional (3-D) matrix depends strongly on the ability of cells to generate traction forces. To overcome the steric hindrance of the matrix, cells need to generate sufficiently high traction forces but also need to distribute these forces spatially in a migration-promoting way. This unit describes a protocol to measure spatial maps of cell traction forces in 3-D biopolymer networks such as collagen, fibrin, or Matrigel. Traction forces are computed from the relationship between measured force-induced matrix deformations surrounding the cell and the known mechanical properties of the matrix. The method does not rely on knowledge of the cell surface coordinates and takes nonlinear mechanical properties of the matrix into account. © 2017 by John Wiley & Sons, Inc.

Quantifying 3D chemotaxis in microfluidic-based chips with step gradients of collagen hydrogel concentrations.

Cell migration is an essential process involved in crucial stages of tissue formation, regeneration or immune function as well as in pathological processes including tumor development or metastasis. During the last few years, the effect of gradients of soluble molecules on cell migration has been widely studied, and complex systems have been used to analyze cell behavior under simultaneous mechano-chemical stimuli. Most of these chemotactic assays have, however, focused on specific substrates in 2D. The aim of the present work is to develop a novel microfluidic-based chip that allows the long-term chemoattractant effect of growth factors (GFs) on 3D cell migration to be studied, while also providing the possibility to analyze the influence of the interface generated between different adjacent hydrogels. Namely, 1.5, 2, 2.5 and 4 mg ml-1 concentrations of collagen type I were alternatively combined with 5, 10 or 50 ng ml-1 concentrations of PDGF and VEGF (as a negative control). To achieve this goal, we have designed a new microfluidic device including three adjacent chambers to introduce hydrogels that allow the generation of a collagen concentration step gradient. This versatile and simple platform was tested by using dermal human fibroblasts embedded in 3D collagen matrices. Images taken over a week were processed to quantify the number of cells in each zone. We found, in terms of cell distribution, that the presence of PDGF, especially in small concentrations, was a strong chemoattractant for dermal human fibroblasts across the gels regardless of their collagen concentration and step gradient direction, whereas the effects of VEGF or collagen step gradient concentrations alone were negligible.

A phenomenological cohesive model for the macroscopic simulation of cell-matrix adhesions.

Cell adhesion is crucial for cells to not only physically interact with each other but also sense their microenvironment and respond accordingly. In fact, adherent cells can generate physical forces that are transmitted to the surrounding matrix, regulating the formation of cell-matrix adhesions. The main purpose of this work is to develop a computational model to simulate the dynamics of cell-matrix adhesions through a cohesive formulation within the framework of the finite element method and based on the principles of continuum damage mechanics. This model enables the simulation of the mechanical adhesion between cell and extracellular matrix (ECM) as regulated by local multidirectional forces and thus predicts the onset and growth of the adhesion. In addition, this numerical approach allows the simulation of the cell as a whole, as it models the complete mechanical interaction between cell and ECM. As a result, we can investigate and quantify how different mechanical conditions in the cell (e.g., contractile forces, actin cytoskeletal properties) or in the ECM (e.g., stiffness, external forces) can regulate the dynamics of cell-matrix adhesions.

Diez años desde el descubrimiento de las células iPS: estado actual de su aplicación clínica / Ten years since the discovery of iPS cells: the current state of their clinical application

Al cumplirse 10 años del descubrimiento de las células pluripotenciales inducidas se revisan los principales resultados en sus distintos campos de aplicación, los obstáculos con los que se ha encontrado su experimentación, así como las posibles aplicaciones en la práctica clínica. La eficacia de las células pluripotenciales inducidas en la experimentación clínica puede equipararse a la de las células troncales embrionarias humanas, pero, a diferencia de estas, no presentan la grave dificultad ética que conlleva la necesidad de destruir embriones humanos para su obtención. El hallazgo de estas células, que constituyó en su día un verdadero hito científico merecedor de un Premio Nobel de Medicina, está hoy rodeado de luces y sombras: grandes esperanzas en la medicina regenerativa frente a riesgos aún no bien controlados de reacciones imprevisibles, tanto en los procesos de desdiferenciación como en la posterior diferenciación hacia las estirpes celulares empleadas con fines terapéuticos o de experimentación (AU)

On the 10-year anniversary of the discovery of induced pluripotent stem cells, we review the main results from their various fields of application, the obstacles encountered during experimentation and the potential applications in clinical practice. The efficacy of induced pluripotent cells in clinical experimentation can be equated to that of human embryonic stem cells; however, unlike stem cells, induced pluripotent cells do not involve the severe ethical difficulties entailed by the need to destroy human embryos to obtain them. The finding of these cells, which was in its day a true scientific milestone worthy of a Nobel Prize in Medicine, is currently enveloped by light and shadow: high hopes for regenerative medicine versus the, as of yet, poorly controlled risks of unpredictable reactions, both in the processes of dedifferentiation and subsequent differentiation to the cell strains employed for therapeutic or experimentation goals (AU)

DNA Detection Reveals Mycobacterium tuberculosis Complex Shedding Routes in Its Wildlife Reservoir the Eurasian Wild Boar.

Since the intensity and frequency of pathogen shedding by hosts determine the probability of infection through direct and indirect contact, the shedding characterization of Mycobacterium tuberculosis complex (MTC) in the key host reservoir in Iberia, the Eurasian wild boar (Sus scrofa), is crucial. We aimed (i) to describe the natural shedding routes of MTC in free-ranging wild boar by a new semi-automated PCR method and (ii) to determine the association of MTC shedding pattern with tuberculosis (TB) progression and individual factors. MTC shedding (by any of the possible routes) was detected in a total of 30.8% (±7.5) out of the sampled individuals with valid or interpretable test results (n = 39). The proportion of TB-positive shedders according to the route was 13.6% (±7.5) for oral swabs, 4.5% (±4.5) for nasal swabs, 4.5% (±4.4) for faecal swabs and 13.6% (±7.5) for individuals being positive to all swabs concomitantly. The probability of shedding mycobacteria (by any route) statistically associated with TB generalization, and the TB score was significantly higher in individuals testing positive to at least one route compared to negatives. Overall, a diversity of shedding routes in wild boar is possible, and it is remarkable that for the first time, the faecal shedding is confirmed for naturally infected wild boar. Our results are consistent with the role wild boar plays for TB maintenance in host communities and environments in Iberia and confirm that it is an important source of mycobacteria infection by different routes. Finally, we evidenced the use of a new PCR technique to detect MTC DNA in excretions can be practical and defined the target routes for sampling wild boar shedding in future studies, such as interventions to control TB in wild boar that can be measured in terms of impact on mycobacteria excretion and transmission (i.e. vaccination).