Metabolic profiling of bacterial co-cultures reveals intermicrobiome interactions and dominant species.

In animal production, the use of probiotic microorganisms has increased since the ban on antibiotic growth promoters in 2006. The added microorganisms interact with the microbiome of the animals, whereby the probiotic activity is not fully understood. Several microorganisms of the genus Bacillus are already known for their probiotic activity and are applied as feed supplements to increase the health status of the animals. They are thought to interact with Escherichia coli, one of the most abundant bacteria in the animal gut. In biotechnological applications, co-culturing enables the regulation of bacterial interaction or the production of target metabolites. The basic principles of multi-imaging high-performance thin-layer chromatography (HPTLC) with upstream cultivation were further developed to analyze the metabolic profiles of three axenic bacilli cultures compared to their co-cultures with E. coli DSM 18039 (K12). The comparative profiling visualized bacteria's metabolic interactions and showed how the presence of E. coli affects the metabolite formation of bacilli. The characteristic metabolic profile images showed not only the influence of microbiomes but also of inoculation, cultivation and nutrients on the commercial probiotic. The formation of antimicrobially active metabolites, detected via three different planar bioassays, was influenced by the presence of other microorganisms, especially in the probiotic. This first application of multi-imaging HPTLC in the field of co-culturing enabled visualization of metabolic interactions of bacteria via their produced chemical as well as bioactive metabolite profiles. The metabolic profiling provided evidence of bacterial interactions, intermicrobiome influences and dominant species in the co-culture.

Bacillus subtilis spores in probiotic feed quantified via bacterial metabolite using planar chromatography.

Interest in probiotics in animal production has increased due to the European ban on antibiotic growth promoters in 2006. Bacillus subtilis DSM 29784 (B. s. 29784) is one such probiotic feed additive used in poultry. Cell counting has been the most common tool for feed analysis, besides flow cytometry and quantitative polymerase chain reaction. However, quantification of the active probiotic in feed is challenging, since results are influenced by cultivation conditions, viable but non-culturable bacteria and the high contents of feed ingredients. This study presents the first quantitative analysis of a metabolite generated by B. s. 29784 spores in feed to draw conclusions on the amount of active dried spores in the feed. Thus, it is the first quantification of active probiotic bacteria at the trace level in feed based on metabolite production but not cell counting. To generate the calibration standards, solutions with different amounts of dried B. s. 29784 spores were cultured under the same conditions as the feed sample, ensuring independence from growth performance. Upstream cultivation, metabolite extraction and high-performance thin-layer chromatography analysis were proven to be highly reliable and reproducible. The repeatability of the method (RSD 1.9%) and the recovery (111% ± 21% in feed additive matrix, 96% ± 13% in ionized feed matrix) were excellent. The variations during cultivation occurred due to the complex spore germination process and presence of other microbes in the feed. This new procedure, detecting only those cells that produced the metabolite of interest, has several advantages as it takes into account bacterial viability, cultivation conditions, spore germination process, growth behavior and the influence of the nutrient-rich feed matrix. It truly reflects the activity of the probiotic in the feed product, allows side-by-side comparison of characteristic metabolite patterns and nutrient consumptions to understand the metabolism of dried spores in matrix.

Strain-specific quantification of probiotic Bacillus subtilis in feed by imaging high-performance thin-layer chromatography.

The European Union has banned the use of antibiotic growth promoters in animal production, which has led to increased use of probiotic microorganisms. These feed additives result in higher costs for farmers, which is why the demand for a quality control system to quantify probiotics in feeds has increased in recent years. Imaging high-performance thin-layer chromatography (HPTLC) was proven to be a robust method for determining the probiotic Bacillus subtilis DSM 29784 strain based on the production of selective bacterial metabolites and thus characteristic metabolite pattern. However, to quantify the specific probiotic strain in the feed, identification of a strain-specific metabolite not produced by genetically very similar bacteria is necessary. Compared to five bacteria with high genetic similarity, a strain-specific metabolite was formed in the probiotic bacteria by a two-step cultivation procedure. Among others, antimicrobial properties were found for this metabolite, which indicated probiotic activity. The hyphenation of normal-phase HPTLC with reversed-phase high-performance liquid chromatography diode array detection and high-resolution mass spectrometry allowed the preliminary assignment of this strain-specific metabolite to the molecular formula C35H44N6O2 (580.3527 Da). This metabolite, produced each time via an upstream cultivation process to generate the standard levels, was used for the quantification of probiotic active cells in the feed. Data on selectivity, linearity, detection limit, recovery, and precision have shown the good performance of the method.

Effects of the Probiotic Activity of Bacillus subtilis DSM 29784 in Cultures and Feeding Stuff.

The European Union banned the usage of antibiotic growth promoters in animal production. The probiotic microorganism of the genus Bacillus appeared to be an attractive candidate to replace antibiotics. The Bacillus subtilis DSM 29784 is one of these strains. To date, the probiotic effect has not been completely understood, but it is supposed that the effect depends on metabolites of the microorganism. Imaging high-performance thin-layer chromatography (HPTLC) is a powerful tool to visualize differences in the metabolite profile of bacteria with high genetic similarity to allow a better understanding of the probiotic effect. In comparison to other bacteria, especially these bacterial cells were more robust to harsh cultivation conditions and produced a higher level of antioxidants or bioactive substances such as surfactin. HPTLC enabled the comparison of pure cell cultures to the spore cultivation in the feed, and the results explain and support the probiotic effect.

Eastern Canada Flocks: images and manually annotated bird positions.

The Eastern Canada (ECA) Flocks data set consists of manually annotated images from the Common Eider (COEI, Somateria mollissima) Winter Survey and the Greater Snow Geese (GSGO, Anser caerulescens atlanticus) Spring Survey. The images were taken in eastern Canada using fixed-wing aircraft and manually annotated with ImageJ's Cell counter plugins. We selected and annotated the ECA Flocks images in order to test the precision of the CountEm flock size estimation method. ECA Flocks includes 179 COEI and 99 GSGO single flock images. We cut each image manually to a rectangle that excluded large parts of the image with no birds. Both versions (original and cut) of each image are available in the data set. We manually annotated 637,555 (124,309 COEI and 514,235 GSGO) bird positions in the cut images from both surveys. Each bird has an associated "Type," which refers to species and/or sex. Sex identification was only possible for adult common eiders, because females and immature males are brown birds, whereas adult males have mainly white plumage. In the COEI images 64,484 males and 58,029 females, as well as 1,796 birds of other species, were identified. In the GSGO images 504,891 Snow Geese and 9,344 birds of other species were labeled. A .csv file including all annotated bird positions and types is available for each image. The COEI and GSGO photos of the ECA Flocks data set were taken in the years 2006 and 2018 and 2016-2018, respectively. We selected these photos in order to include images with different quality and resolution. COEI and GSGO flock sizes range from 6 to 4,154 and from 43 to 36,241 respectively. There is high variability in light conditions, backgrounds, and number and spatial arrangement of birds across the images. The data set is therefore potentially useful to test the precision of methods for analyzing imagery to estimate the abundance of animals by directly detecting, identifying, and counting individuals. We release these data into the public domain under a Creative Commons Zero license waiver. When you use the data in your publication, cite this data paper. Should ECA Flocks be a major part of the data analyzed in your study, you should consider inviting the ECA Flocks originators as collaborators. If you plan to use the ECA Flocks data set, we request that you contact the ECA Flocks core team to learn whether updates are available, and whether similar analyses are already ongoing.

Imaging high-performance thin-layer chromatography as powerful tool to visualize metabolite profiles of eight Bacillus candidates upon cultivation and growth behavior.

Imaging high-performance thin-layer chromatography (HPTLC) was explored with regard to its ability to visualize changes in the metabolite profile of bacteria. Bacillus subtilis has become a model organism in many fields. The increasing interest in these bacteria is driven by their attributed probiotic activity. However, growth behavior and metabolism of Bacillus species have a considerable influence on their activity and secondary metabolite profile. On the HPTLC plate, cultivation broths of Bacillus species (B. subtilis, B. licheniformis, B. pumilus and B. amyloliquefaciens) and some B. subtilis strains of high genetic similarity up to 99.5% were applied directly and compared with their respective liquid-liquid extracts. The latter as well as the cultivation in a minimal medium reduced the matrix load and improved the zone resolution. Cultivation parameters such as nutrient supply, cultivation temperature, cultivation time and rotational speed (oxygen level) as well as medium change were shown to have a considerable influence on the growth behavior and resulting metabolite profiles. Imaging HPTLC turned out to be an efficient and affordable tool to visualize such influences of cultivation parameters on the metabolite profiles. It converts the complexity of reaction processes occurring during cell cultivation in easy-to-understand images, which are helpful to figure out factors of influence and understand activity changes. The results highlighted that optimal cultivation conditions need to be found for the intended bacterial application, and in particular, these conditions have to be kept constant. It must be ensured that small variations in cultivation parameters of bacteria do not change the specified (probiotic) effect on the health of animals and humans. The HPTLC metabolite profiles represented the cultivation conditions of specific bacteria and were found to be a proof of the activity of distinct bacteria. In addition, HPTLC can also be used to optimize and streamline the culture media. The quality control of cultivation or fermentation processes can benefit from such a powerful tool, as a picture is worth a thousand words.

Occupational exposure to cobalt: a population toxicokinetic modeling approach validated by field results challenges the biological exposure index for urinary cobalt.

This study modeled the urinary toxicokinetics of cobalt exposure based on 507 urine samples from 16 workers, followed up for 1 week, and 108 related atmospheric cobalt measurements to determine an optimal urinary cobalt sampling strategy at work and a corresponding urinary exposure threshold (UET). These data have been used to calibrate a population toxicokinetic model, taking into account both the measurement uncertainty and intra- and interindividual variability. Using the calibrated model, urinary sampling sensitivity and specificity performance in detecting exposure above the 20 microg/m(3) threshold limit value - time-weighted average (TLV-TWA) has been applied to identify an optimal urine sampling time. The UET value is obtained by minimizing misclassification rates in workplace exposures below or above the TLV. Total atmospheric cobalt concentrations are in the 5-144 microg/m(3) range, and total urinary cobalt concentrations are 0.5-88 microg/g creatinine. A two-compartment toxicokinetic model best described urinary elimination. Terminal elimination half-time from the central compartment is 10.0 hr (95% confidence interval [8.3-12.3]). The optimal urinary sampling time has been identified as 3 hr before the end of shift at the end of workweek. If we assume that misclassification errors are of equal cost, the UET associated with the TLV of 20 microg/m(3) is 5 microg/L, which is lower than the ACGIH-recommended biological exposure index of 15 microg/L.

Biomonitoring of two types of chromium exposure in an electroplating shop.

OBJECTIVES: This study is concerned with two specific chromium (Cr) exposure situations at a hard-process electroplating company. Its aims are to define variations in urinary Cr concentration and to clarify their exposure relationships. METHODS: Airborne chromium exposure and urinary excretion were measured for a-one week period. The majority of the exposed population was divided into two groups distinguishing chromium plating and polishing functions. Analysis of airborne Cr distinguished water soluble Cr(VI), water total soluble Cr and water insoluble Cr. Volunteers provided 6-7 urine samples per day for a monitoring period of 7 days. RESULTS: Differences between the two groups appear in relation to the type of exposure. Low concentration water soluble Cr(VI) (5.3 microg/m3 maximum) in electroplating shops is practically undetected in other workshops. Water insoluble Cr present in low concentration in electroplating exceeds 1 mg/m3 in polishing shops. Total soluble Cr concentrations are similar in these two activities (3-10 microg/m3). In polishing, 0.4% of the Cr aerosol comprises soluble Cr. Urinary Cr varied according to a 24 h cycle in similar manner in both groups throughout the monitoring week. Minimum values (3-10 microg/g crea) occurred when starting a work shift, following by a rapid rise as soon as exposure commenced, whilst maximum values (12-30 microg/g crea) were recorded towards the end of the work shift. CONCLUSIONS: Although uncorrelated with soluble Cr(VI), urinary Cr (24 h) is effectively related to the soluble fraction of airborne chromium. In the case of chromium electroplating, correspondence between exposure and excretion appears to be governed by relationships different to those emerging from stainless steel welding, from which current biological limit values have been derived.

Specific relationship between blood lead and air lead in the crystal industry.

OBJECTIVES: The main objective of the study was to establish the consequences of exposure to crystal dust on blood lead level in workers employed in hand-finishing and grinding crystal pieces. The second objective was to research a relationship between ambient air lead and blood lead. METHODS: A study conducted in eastern France on 131 subjects occupationally exposed to an aerosol containing crystal particles involved personal measurements of atmospheric exposure to lead, determination of blood lead and, by questionnaire, collection of personal data on exposure characteristics, state of health and level of hygiene of survey volunteers. RESULTS: Initial analysis showed that differences in exposure at the workplace corresponded to differences in blood lead in the operators. There was definitely a potential risk of overexposure to lead, but the existence of this risk was not confirmed by level of blood lead concentrations and, moreover, no clinical signs of lead poisoning in the employees exposed were revealed. The existence of a relationship between personal air (PbA) and blood lead (PbB) levels in grinders and polishers was demonstrated. This relationship, of the form log PbB=2.064+0.181 x log PbA, turns out to be different from those provided by previously published models, which were developed from studies conducted in lead-acid battery manufacturing plants and form the basis of national regulations. Thus, chronic exposure at 100 microg/m(3) of lead at a crystal-grinding workshop corresponds to a mean PbB level of 270 microg/l, whereas the recognized models estimate 350 to 500 microg/l. CONCLUSIONS: This study revealed a specific risk for these categories of exposed individuals. The origin of the descriptive model obtained for the lead exposure/ PbB level relationship raises, through the example of lead, the more general problem of the need to take into account differentiation of chemical substances containing the same element in biological monitoring.