Hanliang Guo

An Activation Force-based Affinity Measure for Analyzing Complex Networks

Affinity measure is a key factor that determines the quality of the analysis of a complex network. Here, we introduce a type of statistics, activation forces, to weight the links of a complex network and thereby develop a desired affinity measure. We show that the approach is superior in facilitating the analysis through experiments on a large-scale word network and a protein-protein interaction (PPI) network consisting of ∼5,000 human proteins. The experiment on the word network verifies that the measured word affinities are highly consistent with human knowledge. Further, the experiment on the PPI network verifies the measure and presents a general method for the identification of functionally similar proteins based on PPIs. Most strikingly, we find an affinity network that compactly connects the cancer-associated proteins to each other, which may reveal novel information for cancer study; this includes likely protein interactions and key proteins in cancer-related signal transduction pathways.

Cilia beating patterns are not hydrodynamically optimal

We examine the hydrodynamic performance of two cilia beating patterns reconstructed from experimental data. In their respective natural systems, the two beating patterns correspond to: (A) pumping-specialized cilia, and (B) swimming-specialized cilia. We compare the performance of these two cilia beating patterns as a function of the metachronal coordination in the context of two model systems: the swimming of a ciliated cylinder and the fluid pumping by a ciliated carpet. Three performance measures are used for this comparison: (i) average swimming speed/pumping flow rate; (ii) maximum internal moments generated by the cilia; and (iii) swimming/pumping efficiencies. We found that, in both models, pattern (B) outperforms pattern (A) in almost all three measures, including hydrodynamic efficiency. These results challenge the notion that hydrodynamic efficiency dictates the cilia beating kinematics, and suggest that other biological functions and constraints play a role in explaining the wide variety of cilia beating patterns observed in biological systems.

Motile cilia create fluid-mechanical microhabitats for the active recruitment of the host microbiome

Significance Recent findings demonstrate that microbiome communities often reside on mucociliated surfaces. While mucociliary clearance of bacteria from such surfaces has been extensively studied, the process of bacterial recruitment has remained unexplored. Here, using a simple model system, we show that ciliated surfaces, in addition to their clearance function, can create fluid-mechanical microhabitats with distinct transport and mixing properties that facilitate the active recruitment of symbiotic candidates from a background of suspended particles. Although each specific system will have unique properties, because ciliary structure and function are highly conserved, studies of models will contribute to an understanding of rules governing the selective behavior of ciliated surfaces. We show that mucociliary membranes of animal epithelia can create fluid-mechanical microenvironments for the active recruitment of the specific microbiome of the host. In terrestrial vertebrates, these tissues are typically colonized by complex consortia and are inaccessible to observation. Such tissues can be directly examined in aquatic animals, providing valuable opportunities for the analysis of mucociliary activity in relation to bacteria recruitment. Using the squid–vibrio model system, we provide a characterization of the initial engagement of microbial symbionts along ciliated tissues. Specifically, we developed an empirical and theoretical framework to conduct a census of ciliated cell types, create structural maps, and resolve the spatiotemporal flow dynamics. Our multiscale analyses revealed two distinct, highly organized populations of cilia on the host tissues. An array of long cilia (∼25 μm) with metachronal beat creates a flow that focuses bacteria-sized particles, at the exclusion of larger particles, into sheltered zones; there, a field of randomly beating short cilia (∼10 μm) mixes the local fluid environment, which contains host biochemical signals known to prime symbionts for colonization. This cilia-mediated process represents a previously unrecognized mechanism for symbiont recruitment. Each mucociliary surface that recruits a microbiome such as the case described here is likely to have system-specific features. However, all mucociliary surfaces are subject to the same physical and biological constraints that are imposed by the fluid environment and the evolutionary conserved structure of cilia. As such, our study promises to provide insight into universal mechanisms that drive the recruitment of symbiotic partners.

Inferring the temporal order of cancer gene mutations in individual tumor samples.

The temporal order of cancer gene mutations in tumors is essential for understanding and treating the disease. Existing methods are unable to infer the order of mutations that are identified at the same time in individual tumor samples, leaving the heterogeneity of the order unknown. Here, we show that through a complex network-based approach, which is based on the newly defined statistic –carcinogenesis information conductivity (CIC), the temporal order in individual samples can be effectively inferred. The results suggest that tumor-suppressor genes might more frequently initiate the order of mutations than oncogenes, and every type of cancer might have its own unique order of mutations. The initial mutations appear to be dedicated to acquiring the function of evading apoptosis, and some order constraints might reflect potential regularities. Our approach is completely data-driven without any parameter settings and can be expected to become more effective as more data will become available.

Evaluating efficiency and robustness in cilia design.

Motile cilia are used by many eukaryotic cells to transport flow. Cilia-driven flows are important to many physiological functions, yet a deep understanding of the interplay between the mechanical structure of cilia and their physiological functions in healthy and diseased conditions remains elusive. To develop such an understanding, one needs a quantitative framework to assess cilia performance and robustness when subject to perturbations in the cilia apparatus. Here we link cilia design (beating patterns) to function (flow transport) in the context of experimentally and theoretically derived cilia models. We particularly examine the optimality and robustness of cilia design. Optimality refers to efficiency of flow transport, while robustness is defined as low sensitivity to variations in the design parameters. We find that suboptimal designs can be more robust than optimal ones. That is, designing for the most efficient cilium does not guarantee robustness. These findings have significant implications on the understanding of cilia design in artificial and biological systems.

Bistability in the synchronization of actuated microfilaments

Cilia and flagella are essential building blocks for biological fluid transport and locomotion at the micron scale. They often beat in synchrony and may transition between different synchronization modes in the same cell type. Here, we investigate the behavior of elastic microfilaments, protruding from a surface and driven at their base by a configuration-dependent torque. We consider full hydrodynamic interactions among and within filaments and no slip at the surface. Isolated filaments exhibit periodic deformations, with increasing waviness and frequency as the magnitude of the driving torque increases. Two nearby but independently-driven filaments synchronize their beating in-phase or anti-phase. This synchrony arises autonomously via the interplay between hydrodynamic coupling and filament elasticity. Importantly, in-phase and anti-phase synchronization modes are bistable and co-exist for a range of driving torques and separation distances. These findings are consistent with experimental observations of in-phase and anti-phase synchronization in the biflagellate \textit{Chlamydomonas reinhardtii} and could have important implications on understanding the biophysical mechanisms underlying transitions between multiple synchronization modes.

A computational study of mucociliary transport in healthy and diseased environments

Abstract Mucociliary clearance is the primary defense mechanism that protects the airways from inhaled toxicants and infectious agents. The fluid medium is spatially non-homogenous, consisting of a viscoelastic mucus layer on top of a nearly-viscous periciliary layer surrounding the motile cilia. In healthy environments, the thickness of the periciliary layer is comparable to the cilia length. Perturbations to this system are directly linked to infection and disease. Clinical evidence links the periciliary layer depletion to reduced rates of mucus clearance. Here, we develop a computational model to systematically study the effects of the viscoelastic properties and thickness of the mucus layer on the system’s performance. We find that, compared to a control case with no mucus, a healthy mucus layer enhances the cilia performance: it improves flow transport at an energetic advantage to the cilia. In contrast, when the periciliary layer is depleted, mucus hinders transport and stiffer mucus leads to a substantial decrease in transport efficiency. This decrease in transport is accompanied by an increase in the cilia internal forces and power needed to complete the cilia beating cycle. We conclude by commenting on the relevance of these findings to understanding mucociliary transport in healthy and diseased environments.