Rewiring of PDZ Domain-Ligand Interaction Network Contributed to Eukaryotic Evolution

PDZ domain-mediated interactions have greatly expanded during metazoan evolution, becoming important for controlling signal flow via the assembly of multiple signaling components. The evolutionary history of PDZ domain-mediated interactions has never been explored at the molecular level. It is of great interest to understand how PDZ domain-ligand interactions emerged and how they become rewired during evolution. Here, we constructed the first human PDZ domain-ligand interaction network (PDZNet) together with binding motif sequences and interaction strengths of ligands. PDZNet includes 1,213 interactions between 97 human PDZ proteins and 591 ligands that connect most PDZ protein-mediated interactions (98%) in a large single network via shared ligands. We examined the rewiring of PDZ domain-ligand interactions throughout eukaryotic evolution by tracing changes in the C-terminal binding motif sequences of the PDZ ligands. We found that interaction rewiring by sequence mutation frequently occurred throughout evolution, largely contributing to the growth of PDZNet. The rewiring of PDZ domain-ligand interactions provided an effective means of functional innovations in nervous system development. Our findings provide empirical evidence for a network evolution model that highlights the rewiring of interactions as a mechanism for the development of new protein functions. PDZNet will be a valuable resource to further characterize the organization of the PDZ domain-mediated signaling proteome

Comparison of spatial distributions of Intracluster light and Dark Matter

In a galaxy cluster, the relative spatial distributions of dark matter, member galaxies, gas, and intracluster light (ICL) may connote their mutual interactions over the cluster evolution. However, it is a challenging problem to provide a quantitative measure for the shape matching between two multi-dimensional scalar distributions. We present a novel methodology, named the {\em Weighted Overlap Coefficient (WOC)}, to quantify the similarity of 2-dimensional spatial distributions. We compare the WOC with a standard method known as the Modified Hausdorff Distance (MHD). We find that our method is robust, and performs well even with the existence of multiple sub-structures. We apply our methodology to search for a visible component whose spatial distribution resembled with that of dark matter. If such a component could be found to trace the dark matter distribution with high fidelity for more relaxed galaxy clusters, then the similarity of the distributions could also be used as a dynamical stage estimator of the cluster. We apply the method to six galaxy clusters at different dynamical stages simulated within the GRT simulation, which is an N-body simulation using the galaxy replacement technique. Among the various components (stellar particles, galaxies, ICL), the ICL+ brightest cluster galaxy (BCG) component most faithfully trace the dark matter distribution. Among the sample galaxy clusters, the relaxed clusters show stronger similarity in the spatial distribution of the dark matter and ICL+BCG than the dynamically young clusters. While the MHD results show weaker trend with the dynamical stages.Comment: 17 pages, 8 figures, accepted in ApJ

BCG alignment with the Locations of Cluster Members and the Large Scale Structure out to 10 R200_{200}

Using a sample of $>200$ clusters, each with typically $100-200$ spectroscopically confirmed cluster members, we search for a signal of alignment between the Position Angle (PA) of the Brightest Cluster Galaxy (BCG) and the distribution of cluster members on the sky about the cluster centre out to projected distances of 3~R$_{200}$. The deep spectroscopy, combined with corrections for spectroscopic incompleteness, makes our sample ideal to determine alignment signal strengths. We also use an SDSS based skeleton of the filamentary Large Scale Structure (LSS), and measure BCG alignment with the location of the LSS skeleton segments on the sky out to projected distances of 10~R$_{200}$. The alignment signal is measured using three separate statistical measures; Rao's spacing test (U), Kuiper's V parameter (V), and the Binomial probability test (P). The significance of the BCG alignment signal with both cluster members and LSS segments is extremely high (1 in a million chance or less to be drawn randomly from a uniform distribution). We investigate a wide set of parameters that may influence the strength of the alignment signal. Clusters with more elliptical-shaped BCGs show stronger alignment with both their cluster members and LSS segments. Also, selecting clusters with closely connected filaments, or using a luminosity-weighted LSS skeleton, increases the alignment signal significantly. Alignment strength decreases with increasing projected distance. Combined, these results provide strong evidence for the growth of clusters and their BCGs by preferential feeding along the direction of the filaments in which they are embedded.Comment: 21 pages, 5 tables, 5 figures ,Accepted to MNRAS, August 202

The Evolutionarily Conserved LIM Homeodomain Protein LIM-4/LHX6 Specifies the Terminal Identity of a Cholinergic and Peptidergic C. elegans Sensory/Inter/Motor Neuron-Type

The expression of specific transcription factors determines the differentiated features of postmitotic neurons. However, the mechanism by which specific molecules determine neuronal cell fate and the extent to which the functions of transcription factors are conserved in evolution are not fully understood. In C. elegans, the cholinergic and peptidergic SMB sensory/inter/motor neurons innervate muscle quadrants in the head and control the amplitude of sinusoidal movement. Here we show that the LIM homeobox protein LIM-4 determines neuronal characteristics of the SMB neurons. In lim-4 mutant animals, expression of terminal differentiation genes, such as the cholinergic gene battery and the flp-12 neuropeptide gene, is completely abolished and thus the function of the SMB neurons is compromised. LIM-4 activity promotes SMB identity by directly regulating the expression of the SMB marker genes via a distinct cis-regulatory motif. Two human LIM-4 orthologs, LHX6 and LHX8, functionally substitute for LIM-4 in C. elegans. Furthermore, C. elegans LIM-4 or human LHX6 can induce cholinergic and peptidergic characteristics in the human neuronal cell lines. Our results indicate that the evolutionarily conserved LIM-4/LHX6 homeodomain proteins function in generation of precise neuronal subtypes

Post-chemotherapy serum anti-Müllerian hormone level predicts ovarian function recovery

In the era of precision medicine, the prediction of ovarian function recovery from chemotherapy-induced amenorrhoea using feasible biological markers may be helpful to optimise the treatment strategy for young patients with hormone receptor-positive breast cancer. The purpose of this study was to investigate the accuracy of post-chemotherapy biological markers for predicting the recovery of ovarian function in breast cancer patients of the ASTRRA trial, with chemotherapy-induced amenorrhoea. Using data of 82 participants from a single institution in the ASTRRA trial, the post-chemotherapy serum levels of the anti-Müllerian hormone (AMH), oestradiol, inhibin B and other clinical factors associated with chemotherapy-induced amenorrhoea were evaluated. Recovery of ovarian function was defined by the resumption of menstruation manifested by vaginal bleeding. Fifty-two patients regained menstruation within 55 months after enrolment. In univariate analysis, <40 years of age (P = 0.009), oestradiol ≥37 pg/mL (P = 0.003) or AMH ≥800 pg/mL (P = 0.026) were associated with recovery of menstruation. On multivariate analysis, oestradiol (hazard ratio: 3.171, 95% CI: 1.306–7.699, P = 0.011) and AMH (hazard ratio: 2.853, 95% CI: 1.011–8.046, P = 0.048) remained as significant independent predictors for resumption of menstruation. The diagnostic accuracy of age, oestradiol and AMH in predicting the resumption of menstruation was 38.3, 23.3 and 86.7%, respectively. In conclusion, post-chemotherapy AMH level might be a relatively accurate predictor of the recovery of ovarian function, presented by resumption of menstruation in breast cancer patients with chemotherapy-induced amenorrhoea

Computational Analysis of the Spatiotemporal Coordination of Polarized PI3K and Rac1 Activities in Micro-Patterned Live Cells

Polarized molecular activities play important roles in guiding the cell toward persistent and directional migration. In this study, the polarized distributions of the activities of phosphatidylinositol 3-kinase (PI3K) and the Rac1 small GTPase were monitored using chimeric fluorescent proteins (FPs) in cells constrained on micro-patterned strips, with one end connecting to a neighboring cell (junction end) and the other end free of cell-cell contact (free end). The recorded spatiotemporal dynamics of the fluorescent intensity from different cells was scaled into a uniform coordinate system and applied to compute the molecular activity landscapes in space and time. The results revealed different polarization patterns of PI3K and Rac1 activity induced by the growth factor stimulation. The maximal intensity of different FPs, and the edge position and velocity at the free end were further quantified to analyze their correlation and decipher the underlying signaling sequence. The results suggest that the initiation of the edge extension occurred before the activation of PI3K, which led to a stable extension of the free end followed by the Rac1 activation. Therefore, the results support a concerted coordination of sequential signaling events and edge dynamics, underscoring the important roles played by PI3K activity at the free end in regulating the stable lamellipodia extension and cell migration. Meanwhile, the quantification methods and accompanying software developed can provide a convenient and powerful computational analysis platform for the study of spatiotemporal molecular distribution and hierarchy in live cells based on fluorescence images

Visualization of Src activity at different compartments of the plasma membrane by FRET imaging

SummaryMembrane compartments function as segregated signaling platforms for different cellular functions. It is not clear how Src is regulated at different membrane compartments. To visualize local Src activity in live cells, a FRET-based Src biosensor was targeted in or outside of lipid rafts at the plasma membrane, via acylation or prenylation modifications on targeting tags either directly fused to the biosensor or coupled to the biosensor through an inducible heterodimerization system. In response to growth factors and pervanadate, the induction of Src activity in rafts was slower and weaker, dependent on actin and possibly its mediated transportation of Src from perinuclear regions to the plasma membrane. In contrast, the induction of Src activity in nonrafts was faster and stronger, dependent on microtubules. Hence, Src activity is differentially regulated via cytoskeleton at different membrane compartments

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing