Automatic segmentation of fluorescence lifetime microscopy images of cells using multiresolution community detection--a first study.

Inspired by a multiresolution community detection based network segmentation method, we suggest an automatic method for segmenting fluorescence lifetime (FLT) imaging microscopy (FLIM) images of cells in a first pilot investigation on two selected images. The image processing problem is framed as identifying segments with respective average FLTs against the background in FLIM images. The proposed method segments a FLIM image for a given resolution of the network defined using image pixels as the nodes and similarity between the FLTs of the pixels as the edges. In the resulting segmentation, low network resolution leads to larger segments, and high network resolution leads to smaller segments. Furthermore, using the proposed method, the mean-square error in estimating the FLT segments in a FLIM image was found to consistently decrease with increasing resolution of the corresponding network. The multiresolution community detection method appeared to perform better than a popular spectral clustering-based method in performing FLIM image segmentation. At high resolution, the spectral segmentation method introduced noisy segments in its output, and it was unable to achieve a consistent decrease in mean-square error with increasing resolution.

Fluorescence lifetime imaging microscopy using near-infrared contrast agents.

Although single-photon fluorescence lifetime imaging microscopy (FLIM) is widely used to image molecular processes using a wide range of excitation wavelengths, the captured emission of this technique is confined to the visible spectrum. Here, we explore the feasibility of utilizing near-infrared (NIR) fluorescent molecular probes with emission >700 nm for FLIM of live cells. The confocal microscope is equipped with a 785 nm laser diode, a red-enhanced photomultiplier tube, and a time-correlated single photon counting card. We demonstrate that our system reports the lifetime distributions of NIR fluorescent dyes, cypate and DTTCI, in cells. In cells labelled separately or jointly with these dyes, NIR FLIM successfully distinguishes their lifetimes, providing a method to sort different cell populations. In addition, lifetime distributions of cells co-incubated with these dyes allow estimate of the dyes' relative concentrations in complex cellular microenvironments. With the heightened interest in fluorescence lifetime-based small animal imaging using NIR fluorophores, this technique further serves as a bridge between in vitro spectroscopic characterization of new fluorophore lifetimes and in vivo tissue imaging.

Estimating gene signals from noisy microarray images.

In oligonucleotide microarray experiments, noise is a challenging problem, as biologists now are studying their organisms not in isolation but in the context of a natural environment. In low photomultiplier tube (PMT) voltage images, weak gene signals and their interactions with the background fluorescence noise are most problematic. In addition, nonspecific sequences bind to array spots intermittently causing inaccurate measurements. Conventional techniques cannot precisely separate the foreground and the background signals. In this paper, we propose analytically based estimation technique. We assume a priori spot-shape information using a circular outer periphery with an elliptical center hole. We assume Gaussian statistics for modeling both the foreground and background signals. The mean of the foreground signal quantifies the weak gene signal corresponding to the spot, and the variance gives the measure of the undesired binding that causes fluctuation in the measurement. We propose a foreground-signal and shape-estimation algorithm using the Gibbs sampling method. We compare our developed algorithm with the existing Mann-Whitney (MW)- and expectation maximization (EM)/iterated conditional modes (ICM)-based methods. Our method outperforms the existing methods with considerably smaller mean-square error (MSE) for all signal-to-noise ratios (SNRs) in computer-generated images and gives better qualitative results in low-SNR real-data images. Our method is computationally relatively slow because of its inherent sampling operation and hence only applicable to very noisy-spot images. In a realistic example using our method, we show that the gene-signal fluctuations on the estimated foreground are better observed for the input noisy images with relatively higher undesired bindings.

Common developmental genome deprogramming in schizophrenia - Role of Integrative Nuclear FGFR1 Signaling (INFS).

The watershed-hypothesis of schizophrenia asserts that over 200 different mutations dysregulate distinct pathways that converge on an unspecified common mechanism(s) that controls disease ontogeny. Consistent with this hypothesis, our RNA-sequencing of neuron committed cells (NCCs) differentiated from established iPSCs of 4 schizophrenia patients and 4 control subjects uncovered a dysregulated transcriptome of 1349 mRNAs common to all patients. Data reveals a global dysregulation of developmental genome, deconstruction of coordinated mRNA networks, and the formation of aberrant, new coordinated mRNA networks indicating a concerted action of the responsible factor(s). Sequencing of miRNA transcriptomes demonstrated an overexpression of 16 miRNAs and deconstruction of interactive miRNA-mRNA networks in schizophrenia NCCs. ChiPseq revealed that the nuclear (n) form of FGFR1, a pan-ontogenic regulator, is overexpressed in schizophrenia NCCs and overtargets dysregulated mRNA and miRNA genes. The nFGFR1 targeted 54% of all human gene promoters and 84.4% of schizophrenia dysregulated genes. The upregulated genes reside within major developmental pathways that control neurogenesis and neuron formation, whereas downregulated genes are involved in oligodendrogenesis. Our results indicate (i) an early (preneuronal) genomic etiology of schizophrenia, (ii) dysregulated genes and new coordinated gene networks are common to unrelated cases of schizophrenia, (iii) gene dysregulations are accompanied by increased nFGFR1-genome interactions, and (iv) modeling of increased nFGFR1 by an overexpression of a nFGFR1 lead to up or downregulation of selected genes as observed in schizophrenia NCCs. Together our results designate nFGFR1 signaling as a potential common dysregulated mechanism in investigated patients and potential therapeutic target in schizophrenia.

Cerebral organoids reveal early cortical maldevelopment in schizophrenia-computational anatomy and genomics, role of FGFR1.

Studies of induced pluripotent stem cells (iPSCs) from schizophrenia patients and control individuals revealed that the disorder is programmed at the preneuronal stage, involves a common dysregulated mRNA transcriptome, and identified Integrative Nuclear FGFR1 Signaling a common dysregulated mechanism. We used human embryonic stem cell (hESC) and iPSC-derived cerebral organoids from four controls and three schizophrenia patients to model the first trimester of in utero brain development. The schizophrenia organoids revealed an abnormal scattering of proliferating Ki67+ neural progenitor cells (NPCs) from the ventricular zone (VZ), throughout the intermediate (IZ) and cortical (CZ) zones. TBR1 pioneer neurons and reelin, which guides cortico-petal migration, were restricted from the schizophrenia cortex. The maturing neurons were abundantly developed in the subcortical regions, but were depleted from the schizophrenia cortex. The decreased intracortical connectivity was denoted by changes in the orientation and morphology of calretinin interneurons. In schizophrenia organoids, nuclear (n)FGFR1 was abundantly expressed by developing subcortical cells, but was depleted from the neuronal committed cells (NCCs) of the CZ. Transfection of dominant negative and constitutively active nFGFR1 caused widespread disruption of the neuro-ontogenic gene networks in hESC-derived NPCs and NCCs. The fgfr1 gene was the most prominent FGFR gene expressed in NPCs and NCCs, and blocking with PD173074 reproduced both the loss of nFGFR1 and cortical neuronal maturation in hESC cerebral organoids. We report for the first time, progression of the cortical malformation in schizophrenia and link it to altered FGFR1 signaling. Targeting INFS may offer a preventive treatment of schizophrenia.