Biology subjects

Long, A. M.

Publications and source records attributed to Long, A. M..

3 recordsLinked to original sources

bioRxiv2023

The super-healing MRL strain promotes muscle growth in muscular dystrophy through a regenerative extracellular matrix

Genetic background shifts the severity of muscular dystrophy. In mice, the DBA/2J strain confers a more severe muscular dystrophy phenotype, whereas the Murphys Roth Large (MRL) strain has "super-healing" properties that reduce fibrosis. A comparative analysis of the Sgcg null model of Limb Girdle Muscular Dystrophy in the DBA/2J versus MRL strain showed the MRL background was associated with greater myofiber regeneration and reduced structural degradation of muscle. Transcriptomic profiling of dystrophic muscle in the DBA/2J and MRL strains indicated strain-dependent expression of the extracellular matrix (ECM) and TGF-{beta} signaling genes. To investigate the MRL ECM, cellular components were removed from dystrophic muscle sections to generate decellularized "myoscaffolds". Decellularized myoscaffolds from dystrophic mice in the protective MRL strain had significantly less deposition of collagen and matrix-bound TGF-{beta}1 and TGF-{beta}3 throughout the matrix, and dystrophic myoscaffolds from the MRL background were enriched in myokines. C2C12 myoblasts were seeded onto decellularized matrices from Sgcg-/- MRL and Sgcg-/- DBA/2J matrices. Acellular myoscaffolds from the dystrophic MRL background induced myoblast differentiation and growth compared to dystrophic myoscaffolds from the DBA/2J matrices. These studies establish that the MRL background also generates its effect through a highly regenerative ECM, which is active even in muscular dystrophy. Brief SummaryThe extracellular matrix of the super-healing MRL mouse strain harbors regenerative myokines that improve skeletal muscle growth and function in muscular dystrophy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/547098v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@18543eborg.highwire.dtl.DTLVardef@2e3386org.highwire.dtl.DTLVardef@138d5ccorg.highwire.dtl.DTLVardef@5c4ef6_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

Myoscaffolds demonstrate differential matrix components across muscular dystrophies

Extracellular matrix (ECM) pathologic remodeling underlies many fibrotic disorders, including muscular dystrophy. Tissue decellularization removes cellular components while leaving behind ECM components. We generated "on-slide" decellularized tissue slices from genetically distinct dystrophic mouse models. The ECM of dystrophin-and sarcoglycan-deficient muscles had marked thrombospondin 4 deposition, while dysferlin-deficient muscle had excess decorin. Annexins A2 and A6 were present on all dystrophic decellularized ECMs, but annexin matrix deposition was excessive in dysferlin-deficient muscular dystrophy. Adeno-associated viral expression of annexin A6 specifically in muscle resulted in annexin A6 deposition throughout the ECM, indicating muscle as a source of this ECM protein. C2C12 myoblasts seeded onto decellularized matrices displayed differential myoblast mobility. Dystrophin-deficient decellularized matrices inhibited myoblast mobility while dysferlin-deficient decellularized matrices enhanced myoblast movement. Myoblasts treated with recombinant annexin A6 increased mobillity similar to that seen on dysferlin-deficient decellularized matrix. These findings demonstrate specific fibrotic signatures elicit effects on myoblast activity. TEASERFibrosis in muscular dystrophy has differential effects on myoblasts HIGHLIGHTSO_LISpatial architecture and composition of the ECM differ across genetically distinct forms of muscular dystrophy, especially with respect to Annexin A6 protein deposition C_LIO_LIMatrix from dystrophin-mediated muscular dystrophy inhibits myoblast movement C_LIO_LIMatrix from dysferlin-deficient muscular dystrophy promotes myoblast motility C_LIO_LIAnnexin A6 was sufficient to enhance myoblast motility C_LI

molecular biology↗

bioRxiv2019

Benchmarking metagenomic marine microbial growth prediction from codon usage bias and peak-to-trough ratios

Growth rates are fundamental to all organisms and essential for characterizing microbial ecologies. Despite this, we do not know the instantaneous nor maximum growth rates of most naturally-occurring microorganisms. Recent reports indicate DNA replication rates can be estimated from metagenomic coverage, and maximum growth rates can be estimated from genomic characteristics. We tested these approaches with native marine bacteria (<0.6 um size fraction) as 10% inoculum grown in unamended virus-free seawater from the San Pedro Channel, California. This allowed microbial growth without grazing and with greatly reduced viral infection. At multiple time points up to 48 h, we sampled for cell abundances and metagenomic analyses. We generated 101 unique Metagenome-assembled genomes (MAGs) including , {beta}, and {gamma} Proteobacteria, Flavobacteria, Actinobacteria, Verrucomicrobia, Marine Group A/SAR406, MGII archaea, and others. We tracked the growth of each as the fraction of total metagenomic reads mapped to each MAG normalized with length, completeness, and total cell counts. Some MAGs did not grow appreciably, but those we could estimate had growth rates ranging from 0.08 to 5.99 d-1; these are the first reported growth rates for several of the groups. These metagenome-determined growth rates, which often changed within experiments, were compared to (a) DNA replication estimates from the peak-to-trough ratio (PTR) as determined by three different approaches, and (b) maximum growth rates predicted from codon usage bias (CUB). For the large majority of taxa, observed growth rates were not correlated to PTR indices (r ~ -0.26 - 0.08), with exceptions being rapidly growing Oceanospirillales and Saccharospirillaceae (r ~ 0.63 - 0.92). However, CUB was moderately well correlated to observed maximum growth rates (r = 0.57). This suggests that maximum growth rates can be reasonably well-estimated from genomic information alone, but current PTR approaches poorly predict actual growth of most marine planktonic bacteria in unamended seawater.

microbiology↗