Biology subjects

Knight, T.

Publications and source records attributed to Knight, T..

24 records · Page 2Linked to original sources

bioRxiv2021

Glia-neuron signaling mediated by two different BMP ligands impacts synaptic growth

The nervous system is a complex network of cells whose interactions provide circuitry necessary for an organism to perceive and move through its environment. Revealing the molecular basis of how neurons and non-neuronal glia communicate is essential for understanding neural development, behavior, and abnormalities of the nervous system. BMP signaling in motor neurons, activated in part by retrograde signals from muscle expressed Gbb (BMP5/6/7) has been implicated in synaptic growth, function and plasticity in Drosophila melanogaster. Through loss-of-function studies, we establish Gbb as a critical mediator of glia to neuron signaling important for proper synaptic growth. Furthermore, the BMP2/4 ortholog, Dpp, expressed in a subset of motor neurons, acts by autocrine signaling to also facilitate neuromuscular junction (NMJ) growth at specific muscle innervation sites. In addition to signaling from glia to motor neurons, autocrine Gbb induces signaling in larval VNC glia which strongly express the BMP type II receptor, Wit. In addition to Dpps autocrine motor neuron signaling, Dpp also engages in paracrine signaling to adjacent glia but not to neighboring motor neurons. In one type of dorsal midline motor neuron, RP2, dpp transcription is under tight regulation, as its expression is under autoregulatory control in RP2 but not aCC neurons. Taken together our findings indicate that bi-directional BMP signaling, mediated by two different ligands, facilitates communication between glia and neurons. Gbb, prominently expressed in glia, and Dpp acting from a discrete set of neurons induce active Smad-dependent BMP signaling to influence bouton number during neuromuscular junction growth.

neuroscience↗

bioRxiv2020

Demographic analysis of Israeli Carpobrotus populations: management strategies and future directions

Carpobrotus species are harmful invaders to coastal areas throughout the world, particularly in Mediterranean habitats. Demographic models are ideally suited to identify and understand population processes and stages in the life cycle of the species that could be most effectively targeted with management. However, parameterizing these models has been limited by the difficulty in accessing the cliff-side locations where its populations are typically found, as well as accurately measuring the growth and spread individuals, which form large, dense mats. This study uses small unmanned aerial vehicles (UAVs, drones) to collect demographic data and parameterize an Integral Projection Model of an Israeli Carpobrotus population. We validated our data set with ground targets of known size. Through the analysis of asymptotic growth rates and population sensitivities and elasticities, we demonstrate that the population at the study site is demographically stable, and that reducing the survival and growth of the largest individuals would have the greatest effect on reducing overall population growth rate. Our results provide a first evaluation of the demography of Carpobrotus, a species of conservation and economic concern, and provide the first stage-based population model of a representative of the Aizoaceae family, thus contributing to our global knowledge on plant population dynamics. In addition, we demonstrate the advantages of using drones for collecting demographic data in understudied habitats such as coastal ecosystems.

ecology↗

bioRxiv2020

Emergence of stable motifs in consumer-resource communities

Understanding how and why complex communities can be stable has preoccupied ecologists for over a century. Data show that real communities tend to exhibit characteristic motifs and topologies. Despite a large body of theory investigating both ecological (niche partitioning) and evolutionary (speciation and extinction) mechanisms, a general explanation for why particular motifs are more common than others remains elusive. Here we develop a mechanistic framework that investigates the set of possible motifs that can emerge under minimal conditions of a nutrient-limited system with no external inputs, and no spatial heterogeneity. Focusing on consumer-resource communities structured by competition and predation, we find that the emergent motifs under these minimal conditions are vertical trophic chains that maximize energy transfer and biomass production. Not only are such motifs stable to perturbations of species abundances, but they are also robust to species additions and removals. Our findings provide a mechanistic explanation for why tri-trophic chains are overrepresented in real food webs. They suggest that, because they maximize energy transfer, and can emerge and persist under minimal conditions, vertical trophic chains may constitute the fundamental architecture of consumer-resource communities.

ecology↗

bioRxiv2020

Structural analysis of the Legionella pneumophila Dot/Icm Type IV Secretion System Core Complex

Legionella pneumophila is an opportunistic pathogen that causes the potentially fatal pneumonia Legionnaires Disease. This infection and subsequent pathology require the Dot/Icm Type IV Secretion System (T4SS) to deliver effector proteins into host cells. Compared to prototypical T4SSs, the Dot/Icm assembly is much larger, containing ~27 different components including a core complex reported to be composed of five proteins: DotC, DotD, DotF, DotG, and DotH. Using single particle cryo-electron microscopy (cryo-EM), we report reconstructions of the core complex of the Dot/Icm T4SS that includes a symmetry mismatch between distinct structural features of the outer membrane cap (OMC) and periplasmic ring (PR). We present models of known core complex proteins, DotC, DotD, and DotH, and two structurally similar proteins within the core complex, DotK and Lpg0657. This analysis reveals the stoichiometry and contact interfaces between the key proteins of the Dot/Icm T4SS core complex and provides a framework for understanding a complex molecular machine.

microbiology↗

bioRxiv2018

A framework for dissecting ecological mechanisms underlying the island species-area relationship

The relationship between an islands size and the number of species on that island--the island species-area relationship (ISAR)--is one of the most well-known patterns in biogeography, and forms the basis for understanding biodiversity loss in response to habitat loss and fragmentation. Nevertheless, there is contention about exactly how to estimate the ISAR, and the influence of the three primary ecological mechanisms--random sampling, disproportionate effects, and heterogeneity-- that drive it. Key to this contention is that estimates of the ISAR are often confounded by sampling and estimates of measures (i.e., island-level species richness) that are not diagnostic of potential mechanisms. Here, we advocate a sampling-explicit approach for disentangling the possible ecological mechanisms underlying the ISAR using parameters derived from individual-based rarefaction curves estimated across spatial scales. If the parameters derived from rarefaction curves at each spatial scale show no relationship with island area, we cannot reject the hypothesis that ISARs result only from random sampling. However, if the derived metrics change with island area, we can reject random sampling as the only operating mechanism, and infer that effects beyond sampling (i.e., disproportionate effects and/or heterogeneity) are also operating. Finally, if parameters indicative of within-island spatial variation in species composition (i.e., {beta}-diversity) increase with island area, we can conclude that intra-island compositional heterogeneity plays a role in driving the ISAR. We illustrate this approach using representative case studies, including oceanic islands, natural island-like patches, and habitat fragments from formerly continuous habitat, illustrating several combinations of underlying mechanisms. This approach will offer insight into the role of sampling and other processes that underpin the ISAR, providing a more complete understanding of how, and some indication of why, patterns of biodiversity respond to gradients in island area.

ecology↗

bioRxiv2018

MoB (Measurement of Biodiversity): a method to separate the scale-dependent effects of species abundance distribution, density, and aggregation on diversity change

O_LILittle consensus has emerged regarding how proximate and ultimate drivers such as productivity, disturbance, and temperature may affect species richness and other aspects of biodiversity. Part of the confusion is that most studies examine species richness at a single spatial scale and ignore how the underlying components of species richness can vary with spatial scale.\nC_LIO_LIWe provide an approach for the measurement of biodiversity (MoB) that decomposes changes in species rarefaction curves into proximate components attributed to: 1) the species abundance distribution, 2) density of individuals, and 3) the spatial arrangement of individuals. We decompose species richness by comparing spatial and nonspatial sample- and individual-based species rarefaction curves that differentially capture the influence of these components to estimate the relative importance of each in driving patterns of species richness change.\nC_LIO_LIWe tested the validity of our method on simulated data, and we demonstrate it on empirical data on plant species richness in invaded and uninvaded woodlands. We integrated these methods into a new R package (mobr).\nC_LIO_LIThe metrics that mobr provides will allow ecologists to move beyond comparisons of species richness in response to ecological drivers at a single spatial scale towards a dissection of the proximate components that determine species richness across scales.\nC_LI

ecology↗