Machine Learning to Quantitate Neutrophil NETosis

We introduce machine learning (ML) to perform classifcation and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate neutrophil NETosis, a recently discovered process involved in multiple human diseases. CNNs achieved \u3e94% in performance accuracy in diferentiating NETotic from non-NETotic cells and vastly facilitated dose-response analysis and screening of the NETotic response in neutrophils from patients. Using only features learned from nuclear morphology, CNNs can distinguish between NETosis and necrosis and between distinct NETosis signaling pathways, making them a precise tool for NETosis detection. Furthermore, by using CNNs and tools to determine object dispersion, we uncovered diferences in NETotic nuclei clustering between major NETosis pathways that is useful in understanding NETosis signaling events. Our study also shows that neutrophils from patients with sickle cell disease were unresponsive to one of two major NETosis pathways. Thus, we demonstrate the design, performance, and implementation of ML tools for rapid quantitative and qualitative cell analysis in basic science

An acetylation-mediated chromatin switch governs H3K4 methylation read-write capability

In nucleosomes, histone N-terminal tails exist in dynamic equilibrium between free/accessible and collapsed/DNA-bound states. The latter state is expected to impact histone N-termini availability to the epigenetic machinery. Notably, H3 tail acetylation (e.g. K9ac, K14ac, K18ac) is linked to increased H3K4me3 engagement by the BPTF PHD finger, but it is unknown if this mechanism has a broader extension. Here, we show that H3 tail acetylation promotes nucleosomal accessibility to other H3K4 methyl readers, and importantly, extends to H3K4 writers, notably methyltransferase MLL1. This regulation is not observed on peptide substrates yet occurs on the cis H3 tail, as determined with fully-defined heterotypic nucleosomes. In vivo, H3 tail acetylation is directly and dynamically coupled with cis H3K4 methylation levels. Together, these observations reveal an acetylation ‘chromatin switch’ on the H3 tail that modulates read-write accessibility in nucleosomes and resolves the long-standing question of why H3K4me3 levels are coupled with H3 acetylation

COE Loss-of-Function Analysis Reveals a Genetic Program Underlying Maintenance and Regeneration of the Nervous System in Planarians

<div><p>Members of the COE family of transcription factors are required for central nervous system (CNS) development. However, the function of COE in the post-embryonic CNS remains largely unknown. An excellent model for investigating gene function in the adult CNS is the freshwater planarian. This animal is capable of regenerating neurons from an adult pluripotent stem cell population and regaining normal function. We previously showed that planarian <i>coe</i> is expressed in differentiating and mature neurons and that its function is required for proper CNS regeneration. Here, we show that <i>coe</i> is essential to maintain nervous system architecture and patterning in intact (uninjured) planarians. We took advantage of the robust phenotype in intact animals to investigate the genetic programs <i>coe</i> regulates in the CNS. We compared the transcriptional profiles of control and <i>coe</i> RNAi planarians using RNA sequencing and identified approximately 900 differentially expressed genes in <i>coe</i> knockdown animals, including 397 downregulated genes that were enriched for nervous system functional annotations. Next, we validated a subset of the downregulated transcripts by analyzing their expression in <i>coe</i>-deficient planarians and testing if the mRNAs could be detected in <i>coe⁺</i> cells. These experiments revealed novel candidate targets of <i>coe</i> in the CNS such as ion channel, neuropeptide, and neurotransmitter genes. Finally, to determine if loss of any of the validated transcripts underscores the <i>coe</i> knockdown phenotype, we knocked down their expression by RNAi and uncovered a set of <i>coe-</i>regulated genes implicated in CNS regeneration and patterning, including orthologs of <i>sodium channel alpha-subunit</i> and <i>pou4</i>. Our study broadens the knowledge of gene expression programs regulated by COE that are required for maintenance of neural subtypes and nervous system architecture in adult animals.</p></div

<i>coe</i> RNAi strongly inhibits the expression of <i>ChAT</i> in intact planarians.

<p>(<b>A–C</b>) <i>coe</i> RNAi-treated animals were processed for fluorescent <i>in situ</i> hybridization (FISH) to <i>ChAT</i> (N = 10 for each treatment), <i>mat</i> (N = 3 control and 4 RNAi planarians), or <i>collagen</i> (N = 7 control and 5 RNAi). White dashed boxes in A denote regions imaged at higher magnification shown in the panels to the right. Black dashed boxes in C denote regions imaged at higher magnification shown in top right insets. (<b>D</b>) RT-qPCR experiments measuring the relative expression of <i>coe</i>, <i>ChAT</i>, <i>mat</i>, or <i>collagen</i> in <i>control(RNAi)</i> or <i>coe(RNAi)</i> planarians following the 6^th RNAi treatment. Graph shows the mean ± s.d. expression levels relative to the controls. *P<0.05, Student's t-test.</p

COE function is required for maintenance of nervous system architecture in uninjured planarians.

<p>(<b>A</b>) Head or tail images from an animal stained with anti-CRMP-2 and processed for FISH to <i>ChAT</i>. CRMP-2 is expressed in axon projections (white arrows) and neuronal cell bodies (yellow arrows; N = 7). (<b>B</b>) Higher magnification image of region denoted by white box in D shows CRMP-2 is detected in <i>ChAT</i>⁺ cell bodies (arrowhead). Nuclei were stained with DAPI (blue). (<b>C–D</b>) Uninjured control and <i>coe(RNAi)</i> planarians labeled with anti-CRMP-2 and anti-β-TUBULIN or processed for <i>in situ</i> hybridization to <i>cintillo</i>. White and yellow arrows point to axon projections and cell bodies, respectively. N = 8 animals for each treatment; 412 and 290 <i>cintillo⁺</i> cells were counted from control and <i>coe(RNAi)</i> animals, respectively. The number in the top right corner indicates the mean ± s.d. of <i>cintillo⁺</i> cells; *P<0.05, Student's t-test. Anterior is up in all panels. Scale bars, A = 200 µm, D = 100 µm, E = 50 µm, and G = 200 µm.</p

Candidate COE targets genes identified in <i>S. mediterranea</i>.

<p>Candidate COE targets genes identified in <i>S. mediterranea</i>.</p

COE function is required for differentiation and maintenance of diverse neuron types.

<p>(<b>A</b>) <i>coe</i> is expressed in lineage-committed neoblasts (<i>smedwi⁺</i>) and early progeny <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004746#pgen.1004746-Cowles1" target="_blank">[24]</a>, and diverse neuron types, including cholinergic (<i>ChAT</i>), GABAergic (<i>gad</i>), octopaminergic (<i>tbh</i>), dopaminergic (<i>th</i>), serotonergic (<i>tph</i>), and neuropeptidergic (<i>cpp-1</i>, <i>npl</i>, <i>spp-18</i>, <i>spp-19</i>, <i>spp-2</i>) neurons. Genes in green were identified in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004746#pgen.1004746-Cowles1" target="_blank">[24]</a>. (<b>B</b>) To gain insights into how loss of COE function contributes to defects in nervous system differentiation, we analyzed the function of genes that were downregulated in <i>coe(RNAi)</i> animals. These analyses identified additional genes required for CNS regeneration (<i>gbrb1</i>, <i>npl</i>, <i>scna-2</i>, <i>scna-3</i>, <i>pou4l-1</i>) and patterning (<i>nkx2l</i>). In <i>coe(RNAi)</i> animals, we also detected upregulated genes enriched for GO terms associated with muscle development (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004746#pgen-1004746-t001" target="_blank">Table 1</a>), suggesting that COE may also function to repress the expression of mesoderm-specific genes.</p

Annotation of genes differentially expressed in <i>coe(RNAi)</i> animals using DAVID software.

<p>Annotation of genes differentially expressed in <i>coe(RNAi)</i> animals using DAVID software.</p

Functional analysis of genes downregulated following <i>coe</i> RNAi.

<p>The number of animals showing the phenotype(s) among the total number examined from at least two independent experiments is indicated in parentheses.</p><p>Functional analysis of genes downregulated following <i>coe</i> RNAi.</p