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Fusarium ranks as one of the worlds most economically destructive and species-rich groups of mycotoxigenic plant pathogens. These ubiquitous molds produce a plethora of toxic secondary metabolites, such as trichothecenes, zearalenone, fumonisins, and enniatins, which pose a significant threat to agricultural biosecurity, food safety, and plant, human and animal health. Fusarial-induced diseases of virtually every economically important plant cost the global agricultural economy multi-billion euro losses annually. Moreover, phylogenetically diverse fusaria, including plant pathogens, cause infections in humans, with those involving the cornea and nails being the most common.

Background Ixodes ricinus constitutes the main European vector tick for the Lyme borreliosis pathogen Borrelia burgdorferi ( sensu lato ), the relapsing fever borrelia Borrelia miyamotoi , as well as Anaplasma phagocytophilum and several Rickettsia species. Under laboratory conditions, a transovarial transmission to the next tick generation is described for Rickettsia spp. and Borrelia spp., especially regarding B. miyamotoi , whereas the efficiency of transovarial transfer under field conditions is largely unstudied. Methods In order to better estimate the potential infection risk by tick larvae for humans and animals, 1500 I. ricinus larvae from 50 collected “nests” (larvae adhering to the flag in a clumped manner) were individually examined for Borrelia , Rickettsia and A. phagocytophilum DNA using quantitative real-time PCR (qPCR). Results Thirty-nine of 50 nests each (78.0%, 95% CI: 64.0–88.5%) were positive for Borrelia spp. and Rickettsia spp. DNA, and in three nests (6.0%, 95% CI: 1.3–16.5%) A.   phagocytophilum DNA was detected. Overall, DNA from at least one pathogen could be detected in 90.0% (45/50, 95% CI: 78.2–96.7%) of the nests. Of the 1500 larvae, 137 were positive for Borrelia spp. DNA (9.1%, 95% CI: 7.7–10.7%), 341 for Rickettsia spp. DNA (22.7%, 95% CI: 20.6–24.9%) and three for A.   phagocytophilum DNA (0.2%, 95% CI: 0–0.6%). Quantity of Borrelia spp. and Anaplasma spp. DNA in positive larvae was low, with 2.7 × 10 0 Borrelia 5S-23S gene copies and 2.4 × 10 1 A. phagocytophilum msp2/p44 gene copies detected on average, while Rickettsia -positive samples contained on average 5.4 × 10 2 gltA gene copies. Coinfections were found in 66.0% (33/50, 95% CI: 51.2–78.8%) of the nests and 8.6% (38/443, 95% CI: 6.1–11.6%) of positive larvae. In fact, larvae had a significantly higher probability of being infected with Borrelia spp. or Rickettsia spp. when both pathogens were present in the nest. Conclusions This study provides evidence for transovarial transmission of Rickettsia spp. and Borrelia spp. in I. ricinus under field conditions, possibly facilitating pathogen persistence in the ecosystem and reducing the dependence on the presence of suitable reservoir hosts. Further studies are needed to prove transovarial transmission and to explain the surprisingly high proportion of nests containing Rickettsia and/or Borrelia DNA-positive larvae compared to infection rates in adult ticks commonly reported in other studies.

Bacterial culture and biochemical testing (CBtest) have been the cornerstone of pathogen identification in the diagnostic microbiology laboratory. With the advent of Sanger sequencing and later, next-generation sequencing, 16S rRNA next-generation sequencing (16SNGS) has been proposed to be a plausible platform for this purpose. Nevertheless, usage of the 16SNGS platform has both advantages and limitations. In addition, transition from the traditional methods of CBtest to 16SNGS requires procurement of costly equipment, timely and sustainable maintenance of these platforms, specific facility infrastructure and technical expertise. All these factors pose a challenge for middle-income countries, more so for countries in the lower middle-income range. In this review, we describe the basis for CBtest and 16SNGS, and discuss the limitations, challenges, advantages and future potential of using 16SNGS for bacterial pathogen identification in diagnostic microbiology laboratories of middle-income countries.

This work focuses on evaluating nucleic acid extraction methods and optimizing lysis buffer components to enhance nucleic acid yield and minimize the impact of potential inhibitors on target gene amplification to improve the detection of causative pathogens and facilitate their integration into diagnostic practice. Aim. To compare nucleic acid extraction methods from patient biological samples and to optimize lysis buffer composition to enhance nucleic acid yield. Methods. Spectrophotometric and fluorometric methods were used to assess the efficiency and quality of nucleic acid extraction. The concentration of the obtained nucleic acids was measured using a Qubit 4 fluorometer. The quality of the extracted nucleic acids was analyzed by electrophoretic separation in agarose gel, which allowed for the assessment of their integrity and the presence of degradation. To evaluate the inhibition of target genes by extraction agents, real-time PCR was applied. Results. Solid-phase extraction using silica-coated magnetic particles demonstrated superior performance compared to liquid-liquid extraction. Optimal lysis conditions were achieved using 2.7 M guanidinium thiocyanate with 30% isopropanol, which enhanced DNA recovery and inhibitor removal. The addition of glycogen-linear polyacrylamide improved DNA precipitation in the liquid-liquid method. Overall, the solid-phase approach showed better amplification efficiency and nucleic acid yield. Conclusions. It was established that solid-phase extraction methods based on silica-coated magnetic carriers are optimal for isolating nucleic acids from patients’ biological samples for pathogen differentiation.

The emergence of drug-resistant bacteria poses a significant challenge to modern medicine. In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged as powerful tools for combating antimicrobial resistance (AMR). This review aims to explore the role of AI/ML in AMR management, with a focus on identifying pathogens, understanding resistance patterns, predicting treatment outcomes, and discovering new antibiotic agents. Recent advancements in AI/ML have enabled the efficient analysis of large datasets, facilitating the reliable prediction of AMR trends and treatment responses with minimal human intervention. ML algorithms can analyze genomic data to identify genetic markers associated with antibiotic resistance, enabling the development of targeted treatment strategies. Additionally, AI/ML techniques show promise in optimizing drug administration and developing alternatives to traditional antibiotics. By analyzing patient data and clinical outcomes, these technologies can assist healthcare providers in diagnosing infections, evaluating their severity, and selecting appropriate antimicrobial therapies. While integration of AI/ML in clinical settings is still in its infancy, advancements in data quality and algorithm development suggest that widespread clinical adoption is forthcoming. In conclusion, AI/ML holds significant promise for improving AMR management and treatment outcome.

Few developments in microbiological diagnostics have had such a rapid impact on species level identification of microorganisms as matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS). Conventional differentiation methods rely on biochemical criteria and require additional pre-testing and lengthy incubation procedures. In comparison, MALDI-TOF MS can identify bacteria and yeast within minutes directly from colonies grown on culture plates. This radically new, methodically simple approach profoundly reduces the cost of consumables and time spent on diagnostics. The reliability and accuracy of the method have been demonstrated in numerous studies and different systems are already commercially available. Novel applications of the system besides microbial species level identification are also being explored. This includes identification of pathogens from positive blood cultures or directly from patient samples, such as urine. Currently, intriguing MALDI-TOF MS developments are being made regarding the phenotypic detection of certain antibiotic resistance mechanisms, e.g., β-lactamases and carbapenemases. This mini review provides an overview of the literature in the field and also includes our own data and experiences gathered from over 4 years of routine MALDI-TOF MS use in a university hospital's microbiological diagnostics facility. [PUBLICATION ABSTRACT]

Precise and rapid identification and characterization of pathogens and antimicrobial resistance patterns are critical for the adequate treatment of infections, which represent an increasing problem in intensive care medicine. The current situation remains far from satisfactory in terms of turnaround times and overall efficacy. Application of an ineffective antimicrobial agent or the unnecessary use of broad-spectrum antibiotics worsens the patient prognosis and further accelerates the generation of resistant mutants. Here, we provide an overview that includes an evaluation and comparison of existing tools used to diagnose bacterial infections, together with a consideration of the underlying molecular principles and technologies. Special emphasis is placed on emerging developments that may lead to significant improvements in point of care detection and diagnosis of multi-resistant pathogens, and new directions that may be used to guide antibiotic therapy.

Watermelon is an economically important crop widely cultivated in Thailand, but its postharvest quality is increasingly threatened by fungal diseases. Between 2024 and 2025, anthracnose and fruit rot symptoms were observed on postharvest watermelon fruits in Northern Thailand. This study aimed to isolate, identify, and confirm the pathogenicity of associated fungal pathogens. Fifteen fungal strains were recovered and identified using morphological characteristics combined with multi-locus phylogenetic analyses. Species of Colletotrichum were determined as causal agents of anthracnose, whereas members of Fusarium and Neocosmospora were associated with fruit rot. Pathogenicity tests confirmed their ability to cause disease, and all pathogens were successfully re-isolated, fulfilling Koch’s postulates. In the fungicide response tests, copper hydroxide inhibited all fungal species except C . truncatum and F . sulawesiense , demonstrating broad-spectrum activity. Colletotrichum truncatum was completely inhibited by benalaxyl-M (4%) + mancozeb (65%), cyproconazole, and difenoconazole, while F. sulawesiense was inhibited only by copper oxychloride. To our knowledge, this study provides the first global report of anthracnose caused by C. siamense and fruit rot caused by F. hainanense , F. sulawesiense , N. ferruginea , and N. suttoniana on watermelon. It is also the first report in Thailand of anthracnose caused by C. chlorophyti and C. truncatum and fruit rot caused by F. oxysporum . These findings enhance disease diagnosis and support the development of more effective postharvest disease management strategies in watermelon production systems.

Background Despite the increasingly recognized eco-epidemiological significance of bats, data from molecular analyses of vector-borne bacteria in bat ectoparasites are lacking from several regions of the Old and New Worlds. Methods During this study, six species of ticks (630 specimens) were collected from bats in Hungary, Romania, Italy, Kenya, South Africa, China, Vietnam and Mexico. DNA was extracted from these ticks and analyzed for vector-borne bacteria with real-time PCRs (screening), as well as conventional PCRs and sequencing (for pathogen identification), based on the amplification of various genetic markers. Results In the screening assays, Rickettsia DNA was only detected in bat soft ticks, whereas Anaplasma phagocytophilum and haemoplasma DNA were present exclusively in hard ticks. Bartonella DNA was significantly more frequently amplified from hard ticks than from soft ticks of bats. In addition to Rickettsia helvetica detected by a species-specific PCR, sequencing identified four Rickettsia species in soft ticks, including a Rickettsia africae -like genotype (in association with a bat species, which is not known to migrate to Africa), three haemotropic Mycoplasma genotypes in Ixodes simplex , and Bartonella genotypes in I. ariadnae and I. vespertilionis . Conclusions Rickettsiae (from both the spotted fever and the R. felis groups) appear to be associated with soft rather than hard ticks of bats, as opposed to bartonellae. Two tick-borne zoonotic pathogens ( R. helvetica and A. phagocytophilum ) have been detected for the first time in bat ticks. The present findings add Asia (China) to the geographical range of R. lusitaniae , as well as indicate the occurrence of R. hoogstraalii in South Africa. This is also the first molecular evidence for the autochthonous occurrence of a R. africae -like genotype in Europe. Bat haemoplasmas, which are closely related to haemoplasmas previously identified in bats in Spain and to “ Candidatus Mycoplasma haemohominis”, are reported here for the first time from Central Europe and from any bat tick.