Spatial mapping of cellular senescence: emerging challenges and opportunities.

Cellular senescence is a well-established driver of aging and age-related diseases. There are many challenges to mapping senescent cells in tissues such as the absence of specific markers and their relatively low abundance and vast heterogeneity. Single-cell technologies have allowed unprecedented characterization of senescence; however, many methodologies fail to provide spatial insights. The spatial component is essential, as senescent cells communicate with neighboring cells, impacting their function and the composition of extracellular space. The Cellular Senescence Network (SenNet), a National Institutes of Health (NIH) Common Fund initiative, aims to map senescent cells across the lifespan of humans and mice. Here, we provide a comprehensive review of the existing and emerging methodologies for spatial imaging and their application toward mapping senescent cells. Moreover, we discuss the limitations and challenges inherent to each technology. We argue that the development of spatially resolved methods is essential toward the goal of attaining an atlas of senescent cells.

Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain.

Methods for acquiring spatially resolved omics data from complex tissues use barcoded DNA arrays of low- to sub-micrometer features to achieve single-cell resolution. However, fabricating such arrays (randomly assembled beads, DNA nanoballs, or clusters) requires sequencing barcodes in each array, limiting cost-effectiveness and throughput. Here, we describe a vastly scalable stamping method to fabricate polony gels, arrays of ∼1-micrometer clonal DNA clusters bearing unique barcodes. By enabling repeatable enzymatic replication of barcode-patterned gels, this method, compared with the sequencing-dependent array fabrication, reduced cost by at least 35-fold and time to approximately 7 h. The gel stamping was implemented with a simple robotic arm and off-the-shelf reagents. We leveraged the resolution and RNA capture efficiency of polony gels to develop Pixel-seq, a single-cell spatial transcriptomic assay, and applied it to map the mouse parabrachial nucleus and analyze changes in neuropathic pain-regulated transcriptomes and cell-cell communication after nerve ligation.

Intelligent Reflecting Surface Assisted Secure Transmission in UAV-MIMO Communication Systems.

This paper studies the intelligent reflecting surface (IRS) assisted secure transmission in unmanned aerial vehicle (UAV) communication systems, where the UAV base station, the legitimate receiver, and the malicious eavesdropper in the system are all equipped with multiple antennas. By deploying an IRS on the facade of a building, the UAV base station can be assisted to realize the secure transmission in this multiple-input multiple-output (MIMO) system. In order to maximize the secrecy rate (SR), the transmit precoding (TPC) matrix, artificial noise (AN) matrix, IRS phase shift matrix, and UAV position are jointly optimized subject to the constraints of transmit power limit, unit modulus of IRS phase shift, and maximum moving distance of UAV. Since the problem is non-convex, an alternating optimization (AO) algorithm is proposed to solve it. Specifically, the TPC matrix and AN covariance matrix are derived by the Lagrange dual method. The alternating direction method of multipliers (ADMM), majorization-minimization (MM), and Riemannian manifold gradient (RCG) algorithms are presented, respectively, to solve the IRS phase shift matrix, and then the performance of the three algorithms is compared. Based on the proportional integral (PI) control theory, a secrecy rate gradient (SRG) algorithm is proposed to iteratively search for the UAV position by following the direction of the secrecy rate gradient. The theoretic analysis and simulation results show that our proposed AO algorithm has a good convergence performance and can increase the SR by 40.5% compared with the method without IRS assistance.

Creating Red Light-Switchable Protein Dimerization Systems as Genetically Encoded Actuators with High Specificity.

Protein dimerization systems controlled by red light with increased tissue penetration depth are a highly needed tool for clinical applications such as cell and gene therapies. However, mammalian applications of existing red light-induced dimerization systems are hampered by limitations of their two components: a photosensory protein (or photoreceptor) which often requires a mammalian exogenous chromophore and a naturally occurring photoreceptor binding protein typically having a complex structure and nonideal binding properties. Here, we introduce an efficient, generalizable method (COMBINES-LID) for creating highly specific, reversible light-induced heterodimerization systems independent of any existing binders to a photoreceptor. It involves a two-step binder screen (phage display and yeast two-hybrid) of a combinatorial nanobody library to obtain binders that selectively engage a light-activated form of a photoswitchable protein or domain not the dark form. Proof-of-principle was provided by engineering nanobody-based, red light-induced dimerization (nanoReD) systems comprising a truncated bacterial phytochrome sensory module using a mammalian endogenous chromophore, biliverdin, and light-form specific nanobodies. Selected nanoReD systems were biochemically characterized, exhibiting low dark activity and high induction specificity, and further demonstrated for the reversible control of protein translocation and activation of gene expression in mice. Overall, COMBINES-LID opens new opportunities for creating genetically encoded actuators for the optical manipulation of biological processes.

mTM-align: a server for fast protein structure database search and multiple protein structure alignment.

With the rapid increase of the number of protein structures in the Protein Data Bank, it becomes urgent to develop algorithms for efficient protein structure comparisons. In this article, we present the mTM-align server, which consists of two closely related modules: one for structure database search and the other for multiple structure alignment. The database search is speeded up based on a heuristic algorithm and a hierarchical organization of the structures in the database. The multiple structure alignment is performed using the recently developed algorithm mTM-align. Benchmark tests demonstrate that our algorithms outperform other peering methods for both modules, in terms of speed and accuracy. One of the unique features for the server is the interplay between database search and multiple structure alignment. The server provides service not only for performing fast database search, but also for making accurate multiple structure alignment with the structures found by the search. For the database search, it takes about 2-5 min for a structure of a medium size (∼300 residues). For the multiple structure alignment, it takes a few seconds for ∼10 structures of medium sizes. The server is freely available at: http://yanglab.nankai.edu.cn/mTM-align/.

mTM-align: an algorithm for fast and accurate multiple protein structure alignment.

Motivation: As protein structure is more conserved than sequence during evolution, multiple structure alignment can be more informative than multiple sequence alignment, especially for distantly related proteins. With the rapid increase of the number of protein structures in the Protein Data Bank, it becomes urgent to develop efficient algorithms for multiple structure alignment. Results: A new multiple structure alignment algorithm (mTM-align) was proposed, which is an extension of the highly efficient pairwise structure alignment program TM-align. The algorithm was benchmarked on four widely used datasets, HOMSTRAD, SABmark_sup, SABmark_twi and SISY-multiple, showing that mTM-align consistently outperforms other algorithms. In addition, the comparison with the manually curated alignments in the HOMSTRAD database shows that the automated alignments built by mTM-align are in general more accurate. Therefore, mTM-align may be used as a reliable complement to construct multiple structure alignments for real-world applications. Availability and implementation: http://yanglab.nankai.edu.cn/mTM-align. Contact: zhng@umich.edu or yangjy@nankai.edu.cn. Supplementary information: Supplementary data are available at Bioinformatics online.