Dataset Information

Leukocyte Populations in Human Preterm and Term Breast Milk Identified by Multicolour Flow Cytometry.

ABSTRACT: Extremely preterm infants are highly susceptible to bacterial infections but breast milk provides some protection. It is unknown if leukocyte numbers and subsets in milk differ between term and preterm breast milk. This study serially characterised leukocyte populations in breast milk of mothers of preterm and term infants using multicolour flow cytometry methods for extended differential leukocyte counts in blood.Sixty mothers of extremely preterm (<28 weeks gestational age), very preterm (28-31 wk), and moderately preterm (32-36 wk), as well as term (37-41 wk) infants were recruited. Colostrum (d2-5), transitional (d8-12) and mature milk (d26-30) samples were collected, cells isolated, and leukocyte subsets analysed using flow cytometry.The major CD45+ leukocyte populations circulating in blood were also detectable in breast milk but at different frequencies. Progression of lactation was associated with decreasing CD45+ leukocyte concentration, as well as increases in the relative frequencies of neutrophils and immature granulocytes, and decreases in the relative frequencies of eosinophils, myeloid and B cell precursors, and CD16- monocytes. No differences were observed between preterm and term breast milk in leukocyte concentration, though minor differences between preterm groups in some leukocyte frequencies were observed.Flow cytometry is a useful tool to identify and quantify leukocyte subsets in breast milk. The stage of lactation is associated with major changes in milk leukocyte composition in this population. Fresh preterm breast milk is not deficient in leukocytes, but shorter gestation may be associated with minor differences in leukocyte subset frequencies in preterm compared to term breast milk.

SUBMITTER: Trend S

PROVIDER: S-EPMC4545889 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Leukocyte Populations in Human Preterm and Term Breast Milk Identified by Multicolour Flow Cytometry.

Trend Stephanie S de Jong Emma E Lloyd Megan L ML Kok Chooi Heen CH Richmond Peter P Doherty Dorota A DA Simmer Karen K Kakulas Foteini F Strunk Tobias T Currie Andrew A

PloS one 20150819 8

<h4>Background</h4>Extremely preterm infants are highly susceptible to bacterial infections but breast milk provides some protection. It is unknown if leukocyte numbers and subsets in milk differ between term and preterm breast milk. This study serially characterised leukocyte populations in breast milk of mothers of preterm and term infants using multicolour flow cytometry methods for extended differential leukocyte counts in blood.<h4>Methods</h4>Sixty mothers of extremely preterm (<28 weeks g ...[more]

PMID: 26288195

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Project description:BackgroundFlow cytometry is a widespread single-cell measurement technology with a multitude of clinical and research applications. Interpretation of flow cytometry data is hard; the instrumentation is delicate and can not render absolute measurements, hence samples can only be interpreted in relation to each other while at the same time comparisons are confounded by inter-sample variation. Despite this, most automated flow cytometry data analysis methods either treat samples individually or ignore the variation by for example pooling the data. A key requirement for models that include multiple samples is the ability to visualize and assess inferred variation, since what could be technical variation in one setting would be different phenotypes in another.ResultsWe introduce BayesFlow, a pipeline for latent modeling of flow cytometry cell populations built upon a Bayesian hierarchical model. The model systematizes variation in location as well as shape. Expert knowledge can be incorporated through informative priors and the results can be supervised through compact and comprehensive visualizations. BayesFlow is applied to two synthetic and two real flow cytometry data sets. For the first real data set, taken from the FlowCAP I challenge, BayesFlow does not only give a gating which would place it among the top performers in FlowCAP I for this dataset, it also gives a more consistent treatment of different samples than either manual gating or other automated gating methods. The second real data set contains replicated flow cytometry measurements of samples from healthy individuals. BayesFlow gives here cell populations with clear expression patterns and small technical intra-donor variation as compared to biological inter-donor variation.ConclusionsModeling latent relations between samples through BayesFlow enables a systematic analysis of inter-sample variation. As opposed to other joint gating methods, effort is put at ensuring that the obtained partition of the data corresponds to actual cell populations, and the result is therefore directly biologically interpretable. BayesFlow is freely available at GitHub.

Dataset Information

Leukocyte Populations in Human Preterm and Term Breast Milk Identified by Multicolour Flow Cytometry.

Publications

Leukocyte Populations in Human Preterm and Term Breast Milk Identified by Multicolour Flow Cytometry.

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