Integrating single-cell RNA-sequencing and functional assays to decipher mammary cell states and lineage hierarchies

The identification and molecular characterization of cellular hierarchies in complex tissues is key to understanding both normal cellular homeostasis and tumorigenesis. The mammary epithelium is a heterogeneous tissue consisting of two main cellular compartments, an outer basal layer containing myoepithelial cells and an inner luminal layer consisting of estrogen receptor-negative (ER−) ductal cells and secretory alveolar cells (in the fully functional differentiated tissue) and hormone-responsive estrogen receptor-positive (ER+) cells. Recent publications have used single-cell RNA-sequencing (scRNA-seq) analysis to decipher epithelial cell differentiation hierarchies in human and murine mammary glands, and reported the identification of new cell types and states based on the expression of the luminal progenitor cell marker KIT (c-Kit). These studies allow for comprehensive and unbiased analysis of the different cell types that constitute a heterogeneous tissue. Here we discuss scRNA-seq studies in the context of previous research in which mammary epithelial cell populations were molecularly and functionally characterized, and identified c-Kit+ progenitors and cell states analogous to those reported in the recent scRNA-seq studies

Transcriptome analysis of mammary epithelial subpopulations identifies novel determinants of lineage commitment and cell fate

Background: Understanding the molecular control of cell lineages and fate determination in complex tissues is key to not only understanding the developmental biology and cellular homeostasis of such tissues but also for our understanding and interpretation of the molecular pathology of diseases such as cancer. The prerequisite for such an understanding is detailed knowledge of the cell types that make up such tissues, including their comprehensive molecular characterisation. In the mammary epithelium, the bulk of the tissue is composed of three cell lineages, namely the basal/myoepithelial, luminal epithelial estrogen receptor positive and luminal epithelial estrogen receptor negative cells. However, a detailed molecular characterisation of the transcriptomic differences between these three populations has not been carried out. Results: A whole transcriptome analysis of basal/myoepithelial cells, luminal estrogen receptor negative cells and luminal estrogen receptor positive cells isolated from the virgin mouse mammary epithelium identified 861, 326 and 488 genes as highly differentially expressed in the three cell types, respectively. Network analysis of the transcriptomic data identified a subpopulation of luminal estrogen receptor negative cells with a novel potential role as non-professional immune cells. Analysis of the data for potential paracrine interacting factors showed that the basal/myoepithelial cells, remarkably, expressed over twice as many ligands and cell surface receptors as the other two populations combined. A number of transcriptional regulators were also identified that were differentially expressed between the cell lineages. One of these, Sox6, was specifically expressed in luminal estrogen receptor negative cells and functional assays confirmed that it maintained mammary epithelial cells in a differentiated luminal cell lineage. Conclusion: The mouse mammary epithelium is composed of three main cell types with distinct gene expression patterns. These suggest the existence of a novel functional cell type within the gland, that the basal/myoepithelial cells are key regulators of paracrine signalling and that there is a complex network of differentially expressed transcription factors controlling mammary epithelial cell fate. These data will form the basis for understanding not only cell fate determination and cellular homeostasis in the normal mammary epithelium but also the contribution of different mammary epithelial cell types to the etiology and molecular pathology of breast disease

Spitzer 24 um Images of Planetary Nebulae

Spitzer MIPS 24 um images were obtained for 36 Galactic planetary nebulae (PNe) whose central stars are hot white dwarfs (WDs) or pre-WDs with effective temperatures of ~100,000 K or higher. Diffuse 24 um emission is detected in 28 of these PNe. The eight non-detections are angularly large PNe with very low H-alpha surface brightnesses. We find three types of correspondence between the 24 um emission and H-alpha line emission of these PNe: six show 24 um emission more extended than H-alpha emission, nine have a similar extent at 24 um and H-alpha, and 13 show diffuse 24 um emission near the center of the H-alpha shell. The sizes and surface brightnesses of these three groups of PNe and the non-detections suggest an evolutionary sequence, with the youngest ones being brightest and the most evolved ones undetected. The 24 um band emission from these PNe is attributed to [O IV] 25.9 um and [Ne V] 24.3 um line emission and dust continuum emission, but the relative contributions of these three components depend on the temperature of the central star and the distribution of gas and dust in the nebula.Comment: 24 pages, 8 figures, to appear in the Astronomical Journal, September issue. Relace previous file; two references are added and typos are correcte

Regulator of G-protein signalling 2 mRNA is differentially expressed in mammary epithelial subpopulations and over-expressed in the majority of breast cancers

To understand which signalling pathways become deregulated in breast cancer, it is necessary to identify functionally significant gene expression patterns in the stem, progenitor, transit amplifying and differentiated cells of the mammary epithelium. We have previously used the markers 33A10, CD24 and Sca-1 to identify mouse mammary epithelial cell subpopulations. We now investigate the relationship between cells expressing these markers and use gene expression microarray analysis to identify genes differentially expressed in the cell populations. METHODS: Freshly isolated primary mouse mammary epithelial cells were separated on the basis of staining with the 33A10 antibody and an alpha-Sca-1 antibody. The populations identified were profiled using gene expression microarray analysis. Gene expression patterns were confirmed on normal mouse and human mammary epithelial subpopulations and were examined in a panel of breast cancer samples and cell lines. RESULTS: Analysis of the separated populations demonstrated that Sca-1- 33A10High stained cells were estrogen receptor alpha (Esr1)- luminal epithelial cells, whereas Sca-1+ 33A10Low/- stained cells were a mix of nonepithelial cells and Esr1+ epithelial cells. Analysis of the gene expression data identified the gene Rgs2 (regulator of G-protein signalling 2) as being highly expressed in the Sca-1- 33A10Low/- population, which included myoepithelial/basal cells. RGS2 has previously been described as a regulator of angiotensin II receptor signalling. Gene expression analysis by quantitative real-time RT-PCR of cells separated on the basis of CD24 and Sca-1 expression confirmed that Rgs2 was more highly expressed in mouse myoepithelial/basal mammary cells than luminal cells. This expression pattern was conserved in normal human breast cells. Functional analysis demonstrated RGS2 to be a modulator of oxytocin receptor signalling. The potential significance of RGS2 expression in breast cancer was demonstrated by semi-quantitative RT-PCR analysis, data mining and quantitative real-time RT-PCR approaches, which showed that RGS2 was expressed in the majority of solid breast cancers at much higher levels than in normal human mammary cells. CONCLUSION: Molecular analysis of prospectively isolated mammary epithelial cells identified RGS2 as a modulator of oxytocin receptor signalling, which is highly expressed in the myoepithelial cells. The RGS2 gene, but not the oxytocin receptor, was also shown to be over-expressed in the majority of breast cancers, identifying the product of this gene, or the pathway(s) it regulates, as potentially significant therapeutic targets

Infrared Spectral Energy Distributions of Nearby Galaxies

The Spitzer Infrared Nearby Galaxies Survey (SINGS) is carrying out a comprehensive multi-wavelength survey on a sample of 75 nearby galaxies. The 1-850um spectral energy distributions are presented using broadband imaging data from Spitzer, 2MASS, ISO, IRAS, and SCUBA. The infrared colors derived from the globally-integrated Spitzer data are generally consistent with the previous generation of models that were developed based on global data for normal star-forming galaxies, though significant deviations are observed. Spitzer's excellent sensitivity and resolution also allow a detailed investigation of the infrared spectral energy distributions for various locations within the three large, nearby galaxies NGC3031 (M81), NGC5194 (M51), and NGC7331. Strong correlations exist between the local star formation rate and the infrared colors f_nu(70um)/f_nu(160um) and f_nu(24um)/f_nu(160um), suggesting that the 24 and 70um emission are useful tracers of the local star formation activity level. Preliminary evidence indicates that variations in the 24um emission, and not variations in the emission from polycyclic aromatic hydrocarbons at 8um, drive the variations in the f_nu(8.0um)/f_nu(24um) colors within NGC3031, NGC5194, and NGC7331. If the galaxy-to-galaxy variations in spectral energy distributions seen in our sample are representative of the range present at high redshift then extrapolations of total infrared luminosities and star formation rates from the observed 24um flux will be uncertain at the factor-of-five level (total range). The corresponding uncertainties using the redshifted 8.0um flux (e.g. observed 24um flux for a z=2 source) are factors of 10-20. Considerable caution should be used when interpreting such extrapolated infrared luminosities.Comment: 32 pages including 16 figures; accepted for publication in the Astrophysical Journa

Exome sequencing identifies variants in FKBP4 that are associated with recurrent fetal loss in humans

Recurrent pregnancy loss (RPL) is defined as two or more consecutive miscarriages and affects an estimated 1.5% of couples trying to conceive. RPL has been attributed to genetic, endocrine, immune and thrombophilic disorders, But many cases remain unexplained. We investigated a Bangladeshi family where the proband experienced 29 consecutive pregnancy losses with no successful pregnancies from three different marriages. Whole exome sequencing identified rare genetic variants in several candidate genes. These were further investigated in Asian and White European RPL cohorts, and in Bangladeshi controls. FKBP4, encoding the immunophilin FK506 binding protein 4, was identified as a plausible candidate, with three further novel variants identified in Asian patients. None were found in European patients or controls. In silico structural studies predicted damaging effects of the variants in the structure-function properties of the FKBP52 protein. These were located domains reported to be involved in Hsp90 binding and peptidyl-prolyl cic-trans isomerase (PPIase) activity. Profound effects on PPIase activity were demonstrated in transiently transfected HEK293 cells comparing wildtype and mutant FKBP4 constructs. Mice lacking Fkbp4 have been previously reported as infertile through implantation failure. This study therefore strongly implicates FKBP4 as associated with fetal losses in humans, particularly in the Asian population. [Abstract copyright: © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].

Less Work, Less Respect: Authors' Perceived Importance of Research Contributions and Their Declared Contributions to Research Articles

BACKGROUND: Attitudes towards authorship are connected with authors' research experience and with knowledge of authorship criteria of International Committee of Medical Journal Editors (ICMJE). The objective of this study was to assess association between authors' perceived importance of contributions for authorship qualification and their participation in manuscripts submitted to a journal. METHODS: Authors (n = 1181) of 265 manuscripts submitted to the Croatian Medical Journal were asked to identify and rate their contribution in the preparation of the submitted manuscript (0-none to 4-full for 11 listed contributions) and the importance of these contributions as authorship qualifications (0-none to 4-full). They were randomly allocated into 3 groups: the first (n = 90 manuscripts, n = 404 authors) first received the contribution disclosure form and then contribution importance-rating questionnaire; the second (n = 88 manuscripts, n = 382 authors) first received the rating questionnaire and then the contribution disclosure form, and the third group (n = 87 manuscripts, n = 395 authors) received both questionnaires at the same time. We compared authors' perception of importance of contribution categories. RESULTS: 1014 (85.9%) authors of 235 manuscripts responded. Authors who declared contribution to a specific category rated it as more important for authorship than those authors who did not contribute to the same category (P>0.005 for all contribution categories, Mann-Withney test). Authors qualifying for ICMJE authorship rated all contribution categories higher than non-qualifying authors. For all contributions, associations between perceived importance of contribution and actual author's contribution were statistically significant. CONCLUSIONS: Authorship seems to be not a normative issue subjective to categorization into criteria, but also a very personal view of the importance and value of one's contributions

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest