Biology subjects

Zhu, M.

Publications and source records attributed to Zhu, M..

6 recordsLinked to original sources

bioRxiv2018

Three-dimensional tissue stiffness mapping in the mouse embryo supports durotaxis during early limb bud morphogenesis

Numerous biophysical hypotheses invoke tissue stiffness as a key parameter for shaping tissue during development and for influencing cell behaviours during disease progression. However, currently available methods are insufficient to test hypotheses that concern the physical properties of bulk tissues. Here we introduce, validate and apply a new 3D magnetic device that generates a uniform magnetic field gradient within a space that is sufficient to accommodate a vertebrate, organ-stage embryo under live conditions. The device allows for rapid, nontoxic measurement of the spatial variation of absolute elastic modulus and viscosity deep within mesenchymal tissues and within epithelia. By applying the device to map the spatiotemporal variation of viscoelastic properties within the early mouse limb bud, we identified an anteriorly biased mesodermal stiffness gradient along which cells move collectively to shape the early bud. Tissue stiffness corresponds to the nascent expression domain of fibronectin that is Wnt5a-dependent. The findings challenge the notion that Wnt5a regulates cell movements by chemotaxis, and raises the possibility that Wnt5a modifies the tissue microenvironment to promote durotaxis in vivo. Importantly, the ability to precisely measure tissue stiffness in 3D has the potential to instigate and refine mechanisms of development and disease progression.

developmental biology↗

bioRxiv2018

Parkinson’s disease-linked Parkin mutations impair glutamatergic synaptic transmission and plasticity

Parkinson's disease (PD)-associated E3 ubiquitin ligase Parkin is enriched at glutamatergic synapses, where it ubiquitinates multiple substrates, suggesting that its mutation/loss-of-function could contribute to the etiology of PD by disrupting excitatory neurotransmission. Here, we evaluate the impact of four common PD-associated Parkin point mutations (T240M, R275W, R334C, G430D) on glutamatergic synaptic function in hippocampal neurons. We find that expression of these point mutants in Parkin-deficient and -null backgrounds alters NMDA and AMPA receptor-mediated currents and cell-surface levels, and prevents the induction of long-term depression. Mechanistically, we demonstrate that Parkin regulates NMDA receptor trafficking through its ubiquitination of GluN1, and that all four mutants are impaired in this ubiquitinating activity. Furthermore, Parkin regulates synaptic AMPA receptor trafficking via its binding and retention of postsynaptic scaffold Homer1, and all mutants are similarly impaired in this capacity. Our findings demonstrate that pathogenic Parkin mutations disrupt glutamatergic synaptic transmission and plasticity by impeding NMDA and AMPA receptor trafficking, and through these effects likely contribute to the pathophysiology of PD in PARK2 patients.

neuroscience↗

bioRxiv2018

Endo-lysosomal sorting and degradation of Tau mediates glucocorticoid-driven hippocampalmalfunction

Emerging studies implicate Tau as an essential mediator of neuronal atrophy and cognitive impairment in Alzheimers disease (AD), yet the factors that precipitate Tau dysfunction in AD are poorly understood. Chronic environmental stress and elevated glucocorticoids (GC), the major stress hormones, are associated with increased risk of AD, and have been shown to trigger intracellular Tau accumulation and downstream Tau-dependent neuronal dysfunction. However, the mechanisms through which stress and GC disrupt Tau clearance and degradation in neurons remain unclear. Here, we demonstrate that Tau undergoes degradation via endolysosomal sorting in a pathway requiring the small GTPase Rab35 and the endosomal sorting complex required for transport (ESCRT) machinery. Furthermore, we find that GC impair Tau degradation by decreasing Rab35 levels, and that AAV-mediated expression of Rab35 in the hippocampus rescues GC-induced Tau accumulation and related neurostructural deficits. These studies indicate that the Rab35/ESCRT pathway is essential for Tau clearance and part of the mechanism through which GC precipitate brain pathology.

neuroscience↗

bioRxiv2018

Oscillatory cortical forces promote three dimensional cell intercalations that shape the mandibular arch

Multiple vertebrate embryonic structures such as organ primordia are composed of a volume of confluent cells. Although mechanisms that shape tissue sheets are increasingly understood, those which shape a volume of cells remain obscure. Here we show 3D mesenchymal cell intercalations, rather than cell divisions and biophysical tissue properties, are essential to shape the mandibular arch of the mouse embryo. Using a genetically encoded vinculin tension sensor, we show that cortical force oscillations promote these intercalations. Genetic loss and gain of function approaches show that Wnt5a functions as a spatial cue to coordinate cell polarity with cytoskeletal oscillation. YAP/TAZ and PIEZO1 serve as downstream effectors of Wnt5a-mediated actomyosin bias and cytosolic calcium transients, respectively, to ensure appropriate tissue form during growth. Our data support oriented 3D cell neighbour exchange as a conserved mechanism driving volumetric morphogenesis.

developmental biology↗

bioRxiv2018

Identification of novel mutations associated with clofazimine resistance in Mycobacterium abscessus

Mycobacterium abscessus (Mab) is a major non-tuberculous mycobacterial (NTM) pathogen responsible for about 80% of all pulmonary infections caused by rapidly growing mycobacteria. Clofazimine is an effective drug active against Mab and shows synergistic activity when given with amikacin, but the mechanism of resistance to clofazimine in Mab is unknown.\n\nObjectiveTo investigate the molecular basis of clofazimine resistance in Mab.\n\nMethodsWe isolated 29 Mab mutants resistant to clofazimine, and subjected them to whole genome sequencing and Sanger sequencing to identify possible mutations associated with clofazimine resistance.\n\nResultsMutations in MAB_2299c gene which encodes possible transcriptional regulatory protein were identified in 23 of the 29 clofazimine-resistant mutants. In addition, 6 mutations in MAB_1483 were found in 21 of the 29 mutants, and one mutation in MAB_0540 was found in 16 of the 29 mutants. Mutations in MAB_0416c, MAB_4099c, MAB_2613, MAB_0409, MAB_1426 were also associated with clofazimine resistance in less frequency. Two identical mutations which are likely to be polymorphisms unrelated to clofazimine resistance were found in MAB_4605c and MAB_4323 in 13 mutants.\n\nConclusionMutations in MAB_2299c, MAB_1483, and MAB_0540 are the major mechanisms of clofazimine resistance in Mab. Future studies are needed to address the role of the identified mutations in clofazimine resistance in Mab, and our findings have implications for developing a rapid molecular test for detecting clofazimine resistance in this organism.

microbiology↗

bioRxiv2017

No major flaws in "Identification of individuals by trait prediction using whole-genome sequencing data"

In a recently published PNAS article, we studied the identifiability of genomic samples using machine learning methods [Lippert et al., 2017]. In a response, Erlich [2017] argued that our work contained major flaws. The main technical critique of Erlich [2017] builds on a simulation experiment that shows that our proposed algorithm, which uses only a genomic sample for identification, performed no better than a strategy that uses demographic variables. Below, we show why this comparison is misleading and provide a detailed discussion of the key critical points in our analyses that have been brought up in Erlich [2017] and in the media. Further, not only faces may be derived from DNA, but a wide range of phenotypes and demographic variables. In this light, the main contribution of Lippert et al. [2017] is an algorithm that identifies genomes of individuals by combining multiple DNA-based predictive models for a myriad of traits.

genomics↗