Juliana Regina Barreiro

Short communication: Identification of subclinical cow mastitis pathogens in milk by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Subclinical mastitis is a common and easily disseminated disease in dairy herds. Its routine diagnosis via bacterial culture and biochemical identification is a difficult and time-consuming process. In this work, we show that matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) allows bacterial identification with high confidence and speed (1 d for bacterial growth and analysis). With the use of MALDI-TOF MS, 33 bacterial culture isolates from milk of different dairy cows from several farms were analyzed, and the results were compared with those obtained by classical biochemical methods. This proof-of-concept case demonstrates the reliability of MALDI-TOF MS bacterial identification, and its increased selectivity as illustrated by the additional identification of coagulase-negative Staphylococcus species and mixed bacterial cultures. Matrix-assisted laser desorption-ionization mass spectrometry considerably accelerates the diagnosis of mastitis pathogens, especially in cases of subclinical mastitis. More immediate and efficient animal management strategies for mastitis and milk quality control in the dairy industry can therefore be applied.

Bacterial identification: from the agar plate to the mass spectrometer

For more than a century, bacteria and fungi have been identified by isolation in culture followed by enzymatic reactions and morphological analyses. The identification of environmental microorganisms, however, remains a challenge because biochemical and staining protocols for bacteria identification are tedious, usually stepwise, can be long (days) and are prone to errors. Molecular techniques based on DNA amplification and/or sequencing provide more secure molecular identification of specific bacteria, but identification based on mass spectrometry (MS), mainly on MALDI-MS, has been shown to be an alternative accurate and fast method able to identify unknown bacteria on the genus, species and even subspecies level based profiles of proteins and peptides derived from whole bacterial cells. Breakthroughs such as non-culture-based identification of bacteria from biological fluids and MS detection of antibiotic resistance have recently been reported. This review provides an overview of the traditional bacterial and fungal identification workflow and discusses the recent introduction of MS as a powerful tool for the identification of microorganisms. Principles and applications of MS, followed by the use of high-quality databases with dedicated algorithms, are discussed for routine microbial diagnostics, mainly in human clinical settings and in veterinary medicine.

Bovine subclinical intramammary infection caused by coagulase-negative staphylococci increases somatic cell count but has no effect on milk yield or composition

The aim of this study was to evaluate the effect of subclinical intramammary infection (IMI) caused by coagulase-negative staphylococci (CNS) as a group and by specific CNS species on milk yield and composition and somatic cell count (SCC) of dairy cows. Selection of cows with IMI caused by CNS was performed by microbiological cultures of composite samples collected from 1,242 dairy cows distributed in 21 dairy herds. After selection of cows, milk yield was measured and milk samples were collected at the mammary quarter level (i.e., 1,140 mammary samples collected from 285 cows) for analysis of milk composition and SCC. In total, 108 isolates of CNS were identified at the species level by PCR-RFLP analysis. Forty-one pairs of contralateral mammary quarters, with and without IMI, were used to evaluate the effect of CNS on milk yield and composition. Mammary quarters infected with CNS had higher geometric mean SCC (306,106 cells/mL) than noninfected contralateral mammary quarters (62,807 cells/mL). Intramammary infection caused by CNS had no effect on milk yield or on contents of fat, crude protein, casein, lactose, total solids, and solids-not-fat. Staphylococcus chromogenes was the most prevalent CNS species in this study and the only species that allowed within-cow evaluation. The IMI caused by S. chromogenes increased SCC but had no effect on milk yield and composition at the quarter level. In conclusion, subclinical mastitis caused by CNS increased the SCC but had no effect on milk yield and composition of dairy cows.

Identification of Coagulase-Negative Staphylococci from Bovine Intramammary Infection by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

ABSTRACT Coagulase-negative staphylococci (CoNS) are among the main pathogens causing bovine intramammary infection (IMI) in many countries. However, one of the limitations related to the specific diagnosis of CoNS is the lack of an accurate, rapid, and convenient method that can differentiate the bacterial species comprising this group. The aim of this study was to evaluate the ability of matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) to accurately identify CoNS species in dairy cow IMI. In addition, the study aimed to determine the frequency of CoNS species causing bovine IMI. A total of 108 bacterial isolates were diagnosed as CoNS by microbiological cultures from two milk samples collected from 21 dairy herds; the first sample was collected at the cow level (i.e., 1,242 composite samples from all quarters), while the second sample was collected at the mammary quarter level (i.e., 1,140 mammary samples collected from 285 cows). After CoNS isolation was confirmed by microbiological culture for both samples, all CoNS isolates (n = 108) were genotypically differentiated by PCR restriction fragment length polymorphism (RFLP) analysis of a partial groEL gene sequence and subjected to the MALDI-TOF MS identification procedure. MALDI-TOF MS correctly identified 103 (95.4%) of the CoNS isolates identified by PCR-RFLP at the species level. Eleven CoNS species isolated from bovine IMI were identified by PCR-RFLP, and the most prevalent species was Staphylococcus chromogenes (n = 80; 74.1%). In conclusion, MALDI-TOF MS may be a reliable alternative method for differentiating CoNS species causing bovine IMI.

Effect of somatic cell count and mastitis pathogens on milk composition in Gyr cows.

BackgroundGyr cows are well adapted to tropical conditions, resistant to some tropical diseases and have satisfactory milk production. However, Gyr dairy herds have a high prevalence of subclinical mastitis, which negatively affects their milk yield and composition. The objectives of this study were (i) to evaluate the effects of seasonality, mammary quarter location (rear x front), mastitis-causing pathogen species, and somatic cell count (SCC) on milk composition in Gyr cows with mammary quarters as the experimental units and (ii) to evaluate the effects of seasonality and somatic cell count (SCC) on milk composition in Gyr cows with cows as the experimental units. A total of 221 lactating Gyr cows from three commercial dairy farms were selected for this study. Individual foremilk quarter samples and composite milk samples were collected once a month over one year from all lactating cows for analysis of SCC, milk composition, and bacteriological culture.ResultsSubclinical mastitis reduced lactose, nonfat solids and total solids content, but no difference was found in the protein and fat content between infected and uninfected quarters. Seasonality influenced milk composition both in mammary quarters and composite milk samples. Nevertheless, there was no effect of mammary quarter position on milk composition. Mastitis-causing pathogens affected protein, lactose, nonfat solids, and total solids content, but not milk fat content. Somatic cell count levels affected milk composition in both mammary quarters and composite samples of milk.ConclusionsIntramammary infections in Gyr cows alter milk composition; however, the degree of change depends on the mastitis-causing pathogen. Somatic cell count is negatively associated with reduced lactose and nonfat solids content in milk. Seasonality significantly affects milk composition, in which the concentration of lactose, fat, protein, nonfat solids and total solids differs between dry and wet seasons in Gyr cows.

Evaluation of somatic cell count thresholds to detect subclinical mastitis in Gyr cows

The objectives of this study were (1) to determine the sensitivity (Se) and specificity (Sp) of somatic cell count (SCC) thresholds to identify subclinical mastitis in Gyr cows caused by major and minor pathogens; (2) to study the effects of month of sampling, rear or front mammary quarters, herd, intramammary infection (IMI), and bacterial species on SCC at quarter level; and (3) to describe the prevalence of IMI in Gyr cows in commercial dairy herds. In total, 221 lactating Gyr cows from 3 commercial dairy farms were selected. Milk samples were collected from individual quarters once a month for 1 yr from all lactating cows for SCC and bacteriological analysis. Mammary quarters were considered the experimental units and the SCC results were log(10)-transformed. Four SCC thresholds (100, 200, 300 and 400 × 10(3) cells/mL) were used to determine Se and Sp to identify infected mammary quarters. The overall prevalence of IMI in quarter milk samples of Gyr cows was 49.8%, and the prevalence of minor pathogens was higher (31.9%) than that of major pathogens (17.8%). Quarter samples with microbial isolation presented higher SCC compared with negative samples. Sensitivity and Sp of selected SCC thresholds varied according to the group of pathogen (major and minor) involved in the IMI definition. Sensitivity increased and Sp decreased when mammary quarters with only major pathogens isolation were considered positive. The use of a single SCC analysis to classify quarters as uninfected or infected in Gyr cows may not be a useful test for this breed because Se and Sp of SCC at the studied thresholds were low. The occurrence of IMI and the bacterial species are the main factors responsible for SCC variation in mammary quarters of Gyr cows. Milk samples with major pathogens isolation elicited higher SCC than those with minor pathogens.

Nonculture-based identification of bacteria in milk by protein fingerprinting.

Traditional methods for bacterial identification include Gram staining, culturing, and biochemical assays for phenotypic characterization of the causative organism. These methods can be time‐consuming because they require in vitro cultivation of the microorganisms. Recently, however, it has become possible to obtain chemical profiles for lipids, peptides, and proteins that are present in an intact organism, particularly now that new developments have been made for the efficient ionization of biomolecules. MS has therefore become the state‐of‐the‐art technology for microorganism identification in microbiological clinical diagnosis. Here, we introduce an innovative sample preparation method for nonculture‐based identification of bacteria in milk. The technique detects characteristic profiles of intact proteins (mostly ribosomal) with the recently introduced MALDI SepsityperTM Kit followed by MALDI‐MS. In combination with a dedicated bioinformatics software tool for databank matching, the method allows for almost real‐time and reliable genus and species identification. We demonstrate the sensitivity of this protocol by experimentally contaminating pasteurized and homogenized whole milk samples with bacterial loads of 103–108 colony‐forming units (cfu) of laboratory strains of Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus. For milk samples contaminated with a lower bacterial load (104 cfu mL−1), bacterial identification could be performed after initial incubation at 37°C for 4 h. The sensitivity of the method may be influenced by the bacterial species and count, and therefore, it must be optimized for the specific application. The proposed use of protein markers for nonculture‐based bacterial identification allows for high‐throughput detection of pathogens present in milk samples. This method could therefore be useful in the veterinary practice and in the dairy industry, such as for the diagnosis of subclinical mastitis and for the sanitary monitoring of raw and processed milk products.

Effects of bovine subclinical mastitis caused by Corynebacterium spp. on somatic cell count, milk yield and composition by comparing contralateral quarters.

Subclinical mastitis caused by Corynebacterium spp. (as a group and at the species level) was investigated by evaluating contralateral (healthy and infected) mammary quarters for somatic cell count (SCC), milk yield and composition. Selection of cows with subclinical mastitis caused by Corynebacterium spp. was performed by microbiological culture of composite samples collected from 1242 dairy cows from 21 dairy herds. For each of the selected cows, milk yield was measured and milk samples were collected at the mammary quarter level (i.e., 1140 mammary samples collected from 285 cows) for analysis of milk composition and SCC. The identification of Corynebacterium spp. isolates was performed by 16S rRNA gene sequencing. One hundred and eighty Corynebacterium spp. isolates were identified, of which 167 (92.77%) were C.bovis and eight (4.44%) non-C.bovis; for five of the Corynebacterium spp. isolates (2.77%), sequencing of 16S rRNA genes did not allow identification at the species level. Mammary quarters infected with Corynebacterium spp. as a group had a higher geometric mean SCC (197,900 cells/mL) than healthy contralateral mammary quarters (85,800 cells/mL). Species of Corynebacterium non-C.bovis were infrequently isolated and did not change SCC, milk yield or milk solid contents when evaluated at the contralateral quarter level. Although C.bovis infection showed no effect on milk yield, fat, protein, casein or total solids in milk, it increased SCC and decreased lactose and milk solids non-fat content.

Identification of Corynebacterium spp. isolated from bovine intramammary infections by matrix-assisted laser desorption ionization-time of flight mass spectrometry

Corynebacterium species (spp.) are among the most frequently isolated pathogens associated with subclinical mastitis in dairy cows. However, simple, fast, and reliable methods for the identification of species of the genus Corynebacterium are not currently available. This study aimed to evaluate the usefulness of matrix-assisted laser desorption ionization/mass spectrometry (MALDI-TOF MS) for identifying Corynebacterium spp. isolated from the mammary glands of dairy cows. Corynebacterium spp. were isolated from milk samples via microbiological culture (n=180) and were analyzed by MALDI-TOF MS and 16S rRNA gene sequencing. Using MALDI-TOF MS methodology, 161 Corynebacterium spp. isolates (89.4%) were correctly identified at the species level, whereas 12 isolates (6.7%) were identified at the genus level. Most isolates that were identified at the species level with 16 S rRNA gene sequencing were identified as Corynebacterium bovis (n=156; 86.7%) were also identified as C. bovis with MALDI-TOF MS. Five Corynebacterium spp. isolates (2.8%) were not correctly identified at the species level with MALDI-TOF MS and 2 isolates (1.1%) were considered unidentified because despite having MALDI-TOF MS scores >2, only the genus level was correctly identified. Therefore, MALDI-TOF MS could serve as an alternative method for species-level diagnoses of bovine intramammary infections caused by Corynebacterium spp.

Non-culture-based identification of mastitis-causing bacteria by MALDI-TOF mass spectrometry

The purpose of this study was to evaluate the detection limit of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for direct identification, without previous microbiological culture, of bovine mastitis-causing bacteria from milk samples. Milk samples (n = 15) were experimentally contaminated with Staphylococcus aureus, Streptococcus uberis, Streptococcus agalactiae, Streptococcus dysgalactiae, and Escherichia coli to have bacterial counts ranging from 103 to 109 cfu/mL. These contaminated milk samples were subjected to a preparation protocol for bacterial ribosomal protein extraction using the MALDI Sepsityper kit (Bruker Daltonik, Bremen, Germany), which allowed MALDI-TOF MS coupled with Biotyper software (Bruker Daltonik) to identify bacterial fingerprints based on intact ribosomal proteins. The ability of MALDI-TOF MS to correctly identify bacterial strains from experimentally contaminated milk (without previous microbiological culture) depended on the bacterial count of the samples and on the species of the bacteria evaluated. Adequate identification at the bacterial species level (score ≥2.0) directly from milk samples required bacterial counts in the following ranges: ≥106 cfu/mL of Staph. aureus, ≥107 cfu/mL of E. coli, and ≥108 cfu/mL of Strep. agalactiae, Strep. dysgalactiae, and Strep. uberis. We concluded that direct identification of mastitis-causing pathogens is possible for Staph. aureus, E. coli, Strep. agalactiae, Strep. dysgalactiae, and Strep. uberis, but correct identification depended on the bacterial count in the milk samples.