Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages

Details of the tissues and cell types sequenced to generate the TxBF RNA-Seq dataset for the sheep gene expression atlas.

<p>Details of the tissues and cell types sequenced to generate the TxBF RNA-Seq dataset for the sheep gene expression atlas.</p

Tissue/cell/pathway association of the 50 largest network clusters in the sheep gene expression atlas dataset.

<p>Tissue/cell/pathway association of the 50 largest network clusters in the sheep gene expression atlas dataset.</p

Hierarchical clustering of the samples included in the sheep gene expression atlas dataset.

<p>Samples of each tissue and cell type from each breed and developmental stage were averaged across individuals for ease of visualisation. The tree was constructed from the Euclidean distances between expression vectors using MEGA v7.0.14 [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006997#pgen.1006997.ref141" target="_blank">141</a>] with the neighbour-joining method and edited in the graphical viewer FigTree v1.4.3 [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006997#pgen.1006997.ref142" target="_blank">142</a>]. Clustering is biologically meaningful and highlights the lack of any significant effect of library type post-correction. Samples are coloured by organ system.</p

Interrogation of the underlying expression profiles allows regions of the graph to be associated with specific tissues or cell types.

<p><b>A</b> A three-dimensional visualisation of a Pearson correlation gene to gene network graph (<i>r</i> = 0.75, MCLi = 2.2). Samples of each tissue and cell type from each breed and developmental stage are averaged across individuals for ease of visualisation. Histograms of the averaged expression profile (averaged across individuals for each tissue and cell type for ease of visualisation) of genes in selected clusters are given on the right: <b>B (i)</b> profile of cluster 5 genes whose expression is highest in macrophages; <b>(ii)</b> profile of cluster 7 genes whose expression is highest in fetal ovary and testes; <b>(iii)</b> or a broader expression pattern associated with a cellular process e.g. oxidative phosphorylation (cluster 15). Note that there may be a degree of variation in the expression pattern of individual genes within a cluster which is masked when average profiles are displayed.</p

The number and percentage of Oar v3.1 protein coding and non-coding genes, with average TPM across all animals > 1 in at least one tissue, in both the TxBF dataset after the Kallisto first and second pass, and after incorporating the existing Texel dataset.

<p>The number and percentage of Oar v3.1 protein coding and non-coding genes, with average TPM across all animals > 1 in at least one tissue, in both the TxBF dataset after the Kallisto first and second pass, and after incorporating the existing Texel dataset.</p

Details of the tissues and cell types sequenced to generate the TxBF RNA-Seq dataset for the sheep gene expression atlas.

<p>Details of the tissues and cell types sequenced to generate the TxBF RNA-Seq dataset for the sheep gene expression atlas.</p

Screenshot of the expression profile of the sheep <i>myostatin</i> (<i>MSTN</i>) gene within the BioGPS online portal.

<p>Expression estimates from the TxBF sheep gene expression atlas dataset are available via the BioGPS database (<a href="http://biogps.org/dataset/BDS_00015/sheep-atlas/" target="_blank">http://biogps.org/dataset/BDS_00015/sheep-atlas/</a>). This provides a searchable database of genes, with expression profiles across tissues and cells for each gene displayed as histograms via the following link, <a href="http://biogps.org/sheepatlas/" target="_blank">http://biogps.org/sheepatlas/</a>. The BioGPS platform supports searching for genes with a similar profile, allows access to the raw data, and links to external resources. It also provides the potential for comparative analysis across species, for example with the expression profiles for pig.</p

Collapsed node visualisation of the sheep gene expression atlas dataset in two-dimensions to illustrate the relative proportion of genes in each cluster.

<p>Includes 3104 nodes and 138,407 edges with a Pearson correlation value of <i>r</i> = 0.75 and an MCL inflation (MCLi) value of 2.2. Nodes are coloured by tissue/cell type or for broader classes organ system. The largest clusters are numbered from 1 to 30 (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006997#pgen.1006997.t003" target="_blank">Table 3</a> for functional annotation). The largest clusters are dominated by either house-keeping genes (1 & 4) or genes associated with transcriptionally rich tissues or cell types, such as brain (2), testes (3) and macrophages (5).</p