Effects of Lipidation on a Proline-Rich Antibacterial Peptide.

The emergence of multidrug-resistant bacteria is a worldwide health problem. Antimicrobial peptides have been recognized as potential alternatives to conventional antibiotics, but still require optimization. The proline-rich antimicrobial peptide Bac7(1-16) is active against only a limited number of Gram-negative bacteria. It kills bacteria by inhibiting protein synthesis after its internalization, which is mainly supported by the bacterial transporter SbmA. In this study, we tested two different lipidated forms of Bac7(1-16) with the aim of extending its activity against those bacterial species that lack SbmA. We linked a C12-alkyl chain or an ultrashort cationic lipopeptide Lp-I to the C-terminus of Bac7(1-16). Both the lipidated Bac-C12 and Bac-Lp-I forms acquired activity at low micromolar MIC values against several Gram-positive and Gram-negative bacteria. Moreover, unlike Bac7(1-16), Bac-C12, and Bac-Lp-I did not select resistant mutants in E. coli after 14 times of exposure to sub-MIC concentrations of the respective peptide. We demonstrated that the extended spectrum of activity and absence of de novo resistance are likely related to the acquired capability of the peptides to permeabilize cell membranes. These results indicate that C-terminal lipidation of a short proline-rich peptide profoundly alters its function and mode of action and provides useful insights into the design of novel broad-spectrum antibacterial agents.

Detection of a streptomycin-resistant Mycobacterium bovis strain through antitubercular drug susceptibility testing of Tunisian Mycobacterium tuberculosis complex isolates from cattle.

BACKGROUND: A rising isolation trend of drug-resistant M. bovis from human clinical cases is documented in the literature. Here we assessed Mycobacterium tuberculosis complex isolates from cattle for drug susceptibility by the gold standard agar proportion method and a simplified resazurin microtitre assay (d-REMA). A total of 38 M. tuberculosis complex strains, including M. bovis (n = 36) and M. caprae (n = 2) isolates, from cattle in Tunisia were tested against isoniazid, rifampin, streptomycin, ethambutol, kanamycin and pyrazinamide. RESULTS: M. caprae isolates were found to be susceptible to all test drugs. All M. bovis strains were resistant to pyrazinamide, as expected. In addition, one M. bovis isolate showed high-level resistance to streptomycin (MIC > 500.0 µg/ml). Concordant results with the two methods were found. The most common target genes associated with streptomycin resistance, namely the rrs, rpsL and gidB genes, were DNA sequenced. A non-synonymous mutation at codon 43 (K43R) was found in the rpsL gene. To the best of our knowledge, this is the first report describing the isolation of a streptomycin-resistant M. bovis isolate from animal origin. CONCLUSIONS: Antitubercular drug susceptibility testing of M. bovis isolates from animals should be performed in settings where bTB is endemic in order to estimate the magnitude of the risk of drug-resistant tuberculosis transmission to humans.

Contextualizing Wastewater-Based surveillance in the COVID-19 vaccination era.

SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.

Co-incidence of BA.1 and BA.2 at the start of Singapore's Omicron wave revealed by Community and University Campus wastewater surveillance.

Wastewater surveillance (WWS) has been globally recognised to be a useful tool in quantifying SARS-CoV-2 RNA at the community and residential levels without biases associated with case-reporting. The emergence of variants of concern (VOCs) have given rise to an unprecedented number of infections even though populations are increasingly vaccinated. This is because VOCs have been reported to possess higher transmissibility and can evade host immune responses. The B.1.1.529 lineage (Omicron) has severely disrupted global plans to return to normalcy. In this study, we developed an allele-specific (AS) RT-qPCR assay which simultaneously targets the stretch of deletions and mutations in the spike protein from position 24-27 for quantitative detection of Omicron BA.2. Together with previous assays that detect mutations associated with Omicron BA.1 (deletion at position 69 and 70) and all Omicron (mutation at position 493 and 498), we report the validation and time series of these assays from September 2021 to May 2022 using influent samples from two wastewater treatment plants and across four University campus sites in Singapore. Viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases, AS RT-qPCR assays revealed co-incidence of Omicron BA.1 and BA.2 on 12 January 2022, almost two months after initial BA.1 detection in South Africa and Botswana. BA.2 became the dominant variant by the end of January 2022 and completely displaced BA.1 by mid-March 2022. University campus sites were similarly positive for BA.1 and/or BA.2 in the same week as first detection at the treatment plants, where BA.2 became rapidly established as the dominant lineage within three weeks. These results corroborate clinical incidence of the Omicron lineages in Singapore and indicate minimal silent circulation prior to January 2022. The subsequent simultaneous spread of both variant lineages followed strategic relaxation of safe management measures upon meeting nationwide vaccination goals.

Making waves: Wastewater surveillance of SARS-CoV-2 in an endemic future.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor the emergence and spread of SARS-CoV-2 infections in populations during the COVID-19 pandemic. Coincident with the global vaccination efforts, the world is also enduring new waves of SARS-CoV-2 variants. Reinfections and vaccine breakthroughs suggest an endemic future where SARS-CoV-2 continues to persist in the general population. In this treatise, we aim to explore the future roles of wastewater surveillance. Practically, WBS serves as a relatively affordable and non-invasive tool for mass surveillance of SARS-CoV-2 infection while minimizing privacy concerns, attributes that make it extremely suited for its long-term usage. In an endemic future, the utility of WBS will include 1) monitoring the trend of viral loads of targets in wastewater for quantitative estimate of changes in disease incidence; 2) sampling upstream for pinpointing infections in neighborhoods and at the building level; 3) integrating wastewater and clinical surveillance for cost-efficient population surveillance; and 4) genome sequencing wastewater samples to track circulating and emerging variants in the population. We further discuss the challenges and future developments of WBS to reduce inconsistencies in wastewater data worldwide, improve its epidemiological inference, and advance viral tracking and discovery as a preparation for the next viral pandemic.

Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities.

Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.

A comparative study of flow cytometry-sorted communities and shotgun viral metagenomics in a Singapore municipal wastewater treatment plant.

Traditional or "bulk" viral enrichment and amplification methods used in viral metagenomics introduce unavoidable bias in viral diversity. This bias is due to shortcomings in existing viral enrichment methods and overshadowing by the more abundant viral populations. To reduce the complexity and improve the resolution of viral diversity, we developed a strategy coupling fluorescence-activated cell sorting (FACS) with random amplification and compared this to bulk metagenomics. This strategy was validated on both influent and effluent samples from a municipal wastewater treatment plant using the Modified Ludzack-Ettinger (MLE) process as the treatment method. We found that DNA and RNA communities generated using bulk samples were mostly different from those derived following FACS for both treatments before and after MLE. Before MLE treatment, FACS identified five viral families and 512 viral annotated contigs. Up to 43% of mapped reads were not detected in bulk samples. Nucleo-cytoplasmic large DNA viral families were enriched to a greater extent in the FACS-coupled subpopulations compared with bulk samples. FACS-coupled viromes captured a single-contig viral genome associated with Anabaena phage, which was not observed in bulk samples or in FACS-sorted samples after MLE. These short metagenomic reads, which were assembled into a high-quality draft genome of 46 kbp, were found to be highly dominant in one of the pre-MLE FACS annotated virome fractions (57.4%). Using bulk metagenomics, we identified that between Primary Settling Tank and Secondary Settling Tank viromes, Virgaviridae, Astroviridae, Parvoviridae, Picobirnaviridae, Nodaviridae, and Iridoviridae were susceptible to MLE treatment. In all, bulk and FACS-coupled metagenomics are complementary approaches that enable a more thorough understanding of the community structure of DNA and RNA viruses in complex environmental samples, of which the latter is critical for increasing the sensitivity of detection of viral signatures that would otherwise be lost through bulk viral metagenomics.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Gut Ruminococcaceae levels at baseline correlate with risk of antibiotic-associated diarrhea.

Antibiotic-associated diarrhea (AAD) affects a significant proportion of patients receiving antibiotics. We sought to understand if differences in the gut microbiome would influence the development of AAD. We administered a 3-day course of amoxicillin-clavulanate to 30 healthy adult volunteers, and analyzed their stool microbiome, using 16S rRNA gene sequencing, at baseline and up to 4 weeks post antibiotic administration. Lower levels of gut Ruminococcaceae were significantly and consistently observed from baseline until day 7 in participants who developed AAD. Overall, participants who developed AAD experienced a greater decrease in microbial diversity. The probability of AAD could be predicted based on qPCR-derived levels of Faecalibacterium prausnitzii at baseline. Our findings suggest that a lack of gut Ruminococcaceae influences development of AAD. Quantification of F. prausnitzii in stool prior to antibiotic administration may help identify patients at risk of AAD, and aid clinicians in devising individualized treatment regimens to minimize such adverse effects.

Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater.

On November 26, 2021, the B.1.1.529 COVID-19 variant was classified as the Omicron variant of concern (VOC). Reports of higher transmissibility and potential immune evasion triggered flight bans and heightened health control measures across the world to stem its distribution. Wastewater-based surveillance has demonstrated to be a useful complement for clinical community-based tracking of SARS-CoV-2 variants. Using design principles of our previous assays that detect SARS-CoV-2 variants (Alpha and Delta), we developed an allele-specific RT-qPCR assay which simultaneously targets the stretch of mutations from Q493R to Q498R for quantitative detection of the Omicron variant in wastewater. We report their validation against 10-month longitudinal samples from the influent of a wastewater treatment plant in Italy. SARS-CoV-2 RNA concentrations and variant frequencies in wastewater determined using these variant assays agree with clinical cases, revealing rapid displacement of the Delta variant by the Omicron variant within three weeks. These variant trends, when mapped against vaccination rates, support clinical studies that found the rapid emergence of SARS-CoV-2 Omicron variant being associated with an infection advantage over Delta in vaccinated persons. These data reinforce the versatility, utility and accuracy of these open-sourced methods using allele-specific RT-qPCR for tracking the dynamics of variant displacement in communities through wastewater for informed public health responses.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. We collected 24-hour composite wastewater samples from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and measured SARS-CoV-2 RNA concentrations using RT-qPCR. We show that the relationship between wastewater viral titers and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater viral titers and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. We find that the WC ratio increases after key events, providing insight into the balance between disease spread and public health response. We also find that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity. These three metrics could complement a framework for integrating wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Wastewater Surveillance of SARS-CoV-2 across 40 U.S. states.

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020.

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Peptide Inhibitors of Bacterial Protein Synthesis with Broad Spectrum and SbmA-Independent Bactericidal Activity against Clinical Pathogens.

Proline-rich antimicrobial peptides (PrAMPs) are promising lead compounds for developing new antimicrobials; however, their narrow spectrum of action is limiting. PrAMPs kill bacteria binding to their ribosomes and inhibiting protein synthesis. In this study, 133 derivatives of the PrAMP Bac7(1-16) were synthesized to identify the crucial residues for ribosome inactivation and antimicrobial activity. Then, five new Bac7(1-16) derivatives were conceived and characterized by antibacterial and membrane permeabilization assays, X-ray crystallography, and molecular dynamics simulations. Some derivatives displayed broad spectrum activity, encompassing Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, and Staphylococcus aureus. Two peptides out of five acquired a weak membrane-perturbing activity while maintaining the ability to inhibit protein synthesis. These derivatives became independent of the SbmA transporter, commonly used by native PrAMPs, suggesting that they obtained a novel route to enter bacterial cells. PrAMP-derived compounds could become new-generation antimicrobials to combat antibiotic-resistant pathogens.

SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases.

Wastewater surveillance represents a complementary approach to clinical surveillance to measure the presence and prevalence of emerging infectious diseases like the novel coronavirus SARS-CoV-2. This innovative data source can improve the precision of epidemiological modeling to understand the penetrance of SARS-CoV-2 in specific vulnerable communities. Here, we tested wastewater collected at a major urban treatment facility in Massachusetts and detected SARS-CoV-2 RNA from the N gene at significant titers (57 to 303 copies per ml of sewage) in the period from 18 to 25 March 2020 using RT-qPCR. We validated detection of SARS-CoV-2 by Sanger sequencing the PCR product from the S gene. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of 25 March. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks.IMPORTANCE Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is orders of magnitude greater than the number of confirmed clinical cases and therefore may significantly impact efforts to understand the case fatality rate and progression of disease. These data may help inform decisions surrounding the advancement or scale-back of social distancing and quarantine efforts based on dynamic wastewater catchment-level estimations of prevalence.

SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increased exponentially from mid-March to mid-April, after which they began to decline. Viral titers in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral titers as a convolution of back-dated new clinical cases with the viral shedding function of an individual. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. Finally, we found that wastewater viral titers at the neighborhood level correlate better with demographic variables than with population size. This work suggests that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.

Design, antimicrobial activity and mechanism of action of Arg-rich ultra-short cationic lipopeptides.

The increasing emergence of multidrug-resistant microorganisms represents one of the greatest challenges in the clinical management of infectious diseases, and requires the development of novel antimicrobial agents. To this aim, we de novo designed a library of Arg-rich ultra-short cationic antimicrobial lipopeptides (USCLs), based on the Arg-X-Trp-Arg-NH2 peptide moiety conjugated with a fatty acid, and investigated their antibacterial potential. USCLs exhibited an excellent antimicrobial activity against clinically pathogenic microorganisms, in particular Gram-positive bacteria, including multidrug resistant strains, with MIC values ranging between 1.56 and 6.25 µg/mL. The capability of the two most active molecules, Lau-RIWR-NH2 and Lau-RRIWRR-NH2, to interact with the bacterial membranes has been predicted by molecular dynamics and verified on liposomes by surface plasmon resonance. Both compounds inhibited the growth of S. aureus even at sub MIC concentrations and induced cell membranes permeabilization by producing visible cell surface alterations leading to a significant decrease in bacterial viability. Interestingly, no cytotoxic effects were evidenced for these lipopeptides up to 50-100 µg/mL in hemolysis assay, in human epidermal model and HaCaT cells, thus highlighting a good cell selectivity. These results, together with the simple composition of USCLs, make them promising lead compounds as new antimicrobials.

Proline-Rich Peptides with Improved Antimicrobial Activity against E. coli, K. pneumoniae, and A. baumannii.

Proline-rich antimicrobial peptides (PrAMPs) are promising agents to combat multi-drug resistant pathogens due to a high antimicrobial activity, yet low cytotoxicity. A library of derivatives of the PrAMP Bac5(1-17) was synthesized and screened to identify which residues are relevant for its activity. In this way, we discovered that two central motifs -PIRXP- cannot be modified, while residues at N- and C- termini tolerated some variations. We found five Bac5(1-17) derivatives bearing 1-5 substitutions, with an increased number of arginine and/or tryptophan residues, exhibiting improved antimicrobial activity and broader spectrum of activity while retaining low cytotoxicity toward eukaryotic cells. Transcription/translation and bacterial membrane permeabilization assays showed that these new derivatives still retained the ability to strongly inhibit bacterial protein synthesis, but also acquired permeabilizing activity to different degrees. These new Bac5(1-17) derivatives therefore show a dual mode of action which could hinder the selection of bacterial resistance against these molecules.

In Vitro Assessment of the Probiotic Potential of Lactococcus lactis LMG 7930 against Ruminant Mastitis-Causing Pathogens.

Mastitis in dairy ruminants is considered to be the most expensive disease to farmers worldwide. Recently, the intramammary infusion of lactic acid bacteria has emerged as a potential new alternative to antibiotics for preventing and treating bovine mastitis. In this study we have investigated in vitro the probiotic potential of Lactococcus lactis LMG 7930, a food-grade and nisin-producing strain, against mastitis-causing pathogens. We have characterized its carbohydrate fermentation and antibiotic susceptibility profiles, cell surface properties and antimicrobial activity, as well as its capabilities to adhere to and inhibit the invasion of pathogens into the bovine mammary epithelial cell line BME-UV1d. We found that L. lactis LMG 7930 was sensitive to tested drugs, according to the EFSA Panel on Additives and Products or Substances used in Animal Feed (FEEDAP), and showed an improved carbohydrate fermentation capacity compared to starter strains. Moreover, the strain exhibited antagonistic properties towards many of the pathogens tested. It presented medium surface hydrophobicity, a low basic property and no electron acceptor capability. It showed low auto-aggregation and no co-aggregation abilities towards any of the tested pathogens. The strain was one of the most adhesive to bovine mammary epithelial cells among tested bacteria, but its internalisation was low. The strain did not affect significantly pathogen invasion; however, a trend to decrease internalization of some pathogens tested was observed. In conclusion, our results suggest that this strain might be a promising candidate for the development of new strategies of mastitis control in ruminants. Future investigations are needed to evaluate its safety and efficacy under field conditions.