dlx and sp6-9 Control Optic Cup Regeneration in a Prototypic Eye

Optic cups are a structural feature of diverse eyes, from simple pit eyes to camera eyes of vertebrates and cephalopods. We used the planarian prototypic eye as a model to study the genetic control of optic cup formation and regeneration. We identified two genes encoding transcription factors, sp6-9 and dlx, that were expressed in the eye specifically in the optic cup and not the photoreceptor neurons. RNAi of these genes prevented formation of visible optic cups during regeneration. Planarian regeneration requires an adult proliferative cell population with stem cell-like properties called the neoblasts. We found that optic cup formation occurred only after migration of progressively differentiating progenitor cells from the neoblast population. The eye regeneration defect caused by dlx and sp6-9 RNAi can be explained by a failure to generate these early optic cup progenitors. Dlx and Sp6-9 genes function as a module during the development of diverse animal appendages, including vertebrate and insect limbs. Our work reveals a novel function for this gene pair in the development of a fundamental eye component, and it utilizes these genes to demonstrate a mechanism for total organ regeneration in which extensive cell movement separates new cell specification from organ morphogenesis.United States. National Institutes of Health (NIH R01GM080639)W. M. Keck FoundationHoward Hughes Medical Institut

Neoblast Specialization in Regeneration of the Planarian Schmidtea mediterranea

Planarians can regenerate any missing body part in a process requiring dividing cells called neoblasts. Historically, neoblasts have largely been considered a homogeneous stem cell population. Most studies, however, analyzed neoblasts at the population rather than the single-cell level, leaving the degree of heterogeneity in this population unresolved. We combined RNA sequencing of neoblasts from wounded planarians with expression screening and identified 33 transcription factors transcribed in specific differentiated cells and in small fractions of neoblasts during regeneration. Many neoblast subsets expressing distinct tissue-associated transcription factors were present, suggesting candidate specification into many lineages. Consistent with this possibility, klf, pax3/7, and FoxA were required for the differentiation of cintillo-expressing sensory neurons, dopamine-β-hydroxylase-expressing neurons, and the pharynx, respectively. Together, these results suggest that specification of cell fate for most-to-all regenerative lineages occurs within neoblasts, with regenerative cells of blastemas being generated from a highly heterogeneous collection of lineage-specified neoblasts.National Institutes of Health (U.S.) (R01GM080639)National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 1122374

Eye Absence Does Not Regulate Planarian Stem Cells during Eye Regeneration

Dividing cells called neoblasts contain pluripotent stem cells and drive planarian flatworm regeneration from diverse injuries. A long-standing question is whether neoblasts directly sense and respond to the identity of missing tissues during regeneration. We used the eye to investigate this question. Surprisingly, eye removal was neither sufficient nor necessary for neoblasts to increase eye progenitor production. Neoblasts normally increase eye progenitor production following decapitation, facilitating regeneration. Eye removal alone, however, did not induce this response. Eye regeneration following eye-specific resection resulted from homeostatic rates of eye progenitor production and less cell death in the regenerating eye. Conversely, large head injuries that left eyes intact increased eye progenitor production. Large injuries also non-specifically increased progenitor production for multiple uninjured tissues. We propose a model for eye regeneration in which eye tissue production by planarian stem cells is not directly regulated by the absence of the eye itself. Keywords: planarian; regeneration; stem cell; eye; tissue turnover; target blind; progenitor; neoblastNational Institutes of Health (U.S.) (Grant R01GM080639

Impact of image segmentation on high-content screening data quality for SK-BR-3 cells

<p>Abstract</p> <p>Background</p> <p>High content screening (HCS) is a powerful method for the exploration of cellular signalling and morphology that is rapidly being adopted in cancer research. HCS uses automated microscopy to collect images of cultured cells. The images are subjected to segmentation algorithms to identify cellular structures and quantitate their morphology, for hundreds to millions of individual cells. However, image analysis may be imperfect, especially for "HCS-unfriendly" cell lines whose morphology is not well handled by current image segmentation algorithms. We asked if segmentation errors were common for a clinically relevant cell line, if such errors had measurable effects on the data, and if HCS data could be improved by automated identification of well-segmented cells.</p> <p>Results</p> <p>Cases of poor cell body segmentation occurred frequently for the SK-BR-3 cell line. We trained classifiers to identify SK-BR-3 cells that were well segmented. On an independent test set created by human review of cell images, our optimal support-vector machine classifier identified well-segmented cells with 81% accuracy. The dose responses of morphological features were measurably different in well- and poorly-segmented populations. Elimination of the poorly-segmented cell population increased the purity of DNA content distributions, while appropriately retaining biological heterogeneity, and simultaneously increasing our ability to resolve specific morphological changes in perturbed cells.</p> <p>Conclusion</p> <p>Image segmentation has a measurable impact on HCS data. The application of a multivariate shape-based filter to identify well-segmented cells improved HCS data quality for an HCS-unfriendly cell line, and could be a valuable post-processing step for some HCS datasets.</p

Optimization of total protein and activity assays for the detection of MMP-12 in induced human sputum

<p>Abstract</p> <p>Background</p> <p>Proteolysis of matrix components, in particular elastin, is a major contributing factor to the development of lung diseases such as emphysema and chronic obstructive pulmonary disease (COPD). MMP-12 (macrophage elastase) is a protease known to be involved in the progression of lung disease. The relatively low abundance of MMP-12 has precluded the development of quantitative assays that can accurately measure MMP-12 protein levels and activity across cohorts of healthy and diseased individuals.</p> <p>Methods</p> <p>Commercial antibodies were screened for performance in sandwich ELISA and capture FRET activity assay formats. Precision, accuracy, sensitivity, dilution linearity, and spike recovery were evaluated using sputum samples.</p> <p>Results</p> <p>Total protein and capture FRET activity assays were developed that were sensitive enough to detect MMP-12 in 37 of 38 donor sputum samples. A comparison of results between the two assays shows that a majority of sputum MMP-12 is in the active form. No differences were seen between normal, asthmatic, and COPD donors.</p> <p>Conclusion</p> <p>Sensitive and quantitative assays for both MMP-12 activity and total protein in human induced sputum have been developed. These assays can be used to evaluate MMP-12 as a biomarker for lung disease, and to monitor efficacy of potential therapeutic compounds.</p

Image-Based Assessment of Growth and Signaling Changes in Cancer Cells Mediated by Direct Cell-Cell Contact

Many important biological processes are controlled through cell-cell interactions, including the colonization of metastatic tumor cells and the control of differentiation of stem cells within their niche. Despite the crucial importance of the cellular environment in regulating cellular signaling, in vitro methods for the study of such interactions are difficult and/or indirect.We report on the development of an image-based method for distinguishing two cell types grown in coculture. Furthermore, cells of one type that are in direct contact with cells of a second type (adjacent cells) can be analyzed separately from cells that are not within a single well. Changes are evaluated using population statistics, which are useful in detecting subtle changes across two populations. We have used this system to characterize changes in the LNCaP prostate carcinoma cell line when grown in contact with human vascular endothelial cells (HUVECs). We find that the expression and phosphorylation of WWOX is reduced in LNCaP cells when grown in direct contact with HUVECs. Reduced WWOX signaling has been associated with reduced activation or expression of JNK and p73. We find that p73 levels are also reduced in LNCaP cells grown in contact with HUVECs, but we did not observe such a change in JNK levels.We find that the method described is statistically robust and can be adapted to a wide variety of studies where cell function or signaling are affected by heterotypic cell-cell contact. Ironically, a potential challenge to the method is its high level of sensitivity is capable of classifying events as statistically significant (due to the high number cells evaluated individually), when the biological effect may be less clear. The methodology would be best used in conjunction with additional methods to evaluate the biological role of potentially subtle differences between populations. However, many important events, such as the establishment of a metastatic tumor, occur through rare but important changes, and methods such as we describe here can be used to identify and characterize the contribution of the environment to these changes

CATO: The Clone Alignment Tool.

High-throughput cloning efforts produce large numbers of sequences that need to be aligned, edited, compared with reference sequences, and organized as files and selected clones. Different pieces of software are typically required to perform each of these tasks. We have designed a single piece of software, CATO, the Clone Alignment Tool, that allows a user to align, evaluate, edit, and select clone sequences based on comparisons to reference sequences. The input and output are designed to be compatible with standard data formats, and thus suitable for integration into a clone processing pipeline. CATO provides both sequence alignment and visualizations to facilitate the analysis of cloning experiments. The alignment algorithm matches each of the relevant candidate sequences against each reference sequence. The visualization portion displays three levels of matching: 1) a top-level summary of the top candidate sequences aligned to each reference sequence, 2) a focused alignment view with the nucleotides of matched sequences displayed against one reference sequence, and 3) a pair-wise alignment of a single reference and candidate sequence pair. Users can select the minimum matching criteria for valid clones, edit or swap reference sequences, and export the results to a summary file as part of the high-throughput cloning workflow

Sequences can be edited.

<p>Right clicking on the reference sequence (N) allows the full range of sequence modifications.</p

Change the reference sequence.

<p>Right-clicking a candidate sequence (A) results in an orange check mark in the “Use for Ref Seq” column. After such changes, the alignment needs to be saved and rerun, after which the selected clone sequence will become a reference sequence and the previous reference sequence will become a candidate sequence. (B) The same view as (A) with the new reference sequence now being utilized. Ambiguities are resolved and the original single-base deletion is restored resulting in correction of the reading frame.</p