An ancient spliceosomal intron in the ribosomal protein L7a gene (Rpl7a) of Giardia lamblia

BACKGROUND: Only one spliceosomal-type intron has previously been identified in the unicellular eukaryotic parasite, Giardia lamblia (a diplomonad). This intron is only 35 nucleotides in length and is unusual in possessing a non-canonical 5' intron boundary sequence, CT, instead of GT. RESULTS: We have identified a second spliceosomal-type intron in G. lamblia, in the ribosomal protein L7a gene (Rpl7a), that possesses a canonical GT 5' intron boundary sequence. A comparison of the two known Giardia intron sequences revealed extensive nucleotide identity at both the 5' and 3' intron boundaries, similar to the conserved sequence motifs recently identified at the boundaries of spliceosomal-type introns in Trichomonas vaginalis (a parabasalid). Based on these observations, we searched the partial G. lamblia genome sequence for these conserved features and identified a third spliceosomal intron, in an unassigned open reading frame. Our comprehensive analysis of the Rpl7a intron in other eukaryotic taxa demonstrates that it is evolutionarily conserved and is an ancient eukaryotic intron. CONCLUSION: An analysis of the phylogenetic distribution and properties of the Rpl7a intron suggests its utility as a phylogenetic marker to evaluate particular eukaryotic groupings. Additionally, analysis of the G. lamblia introns has provided further insight into some of the conserved and unique features possessed by the recently identified spliceosomal introns in related organisms such as T. vaginalis and Carpediemonas membranifera

Mesenchymal Stem Cells Shift Mitochondrial Dynamics and Enhance Oxidative Phosphorylation in Recipient Cells

Mesenchymal stem cells (MSCs) are the most commonly used cells in tissue engineering and regenerative medicine. MSCs can promote host tissue repair through several different mechanisms including donor cell engraftment, release of cell signaling factors, and the transfer of healthy organelles to the host. In the present study, we examine the specific impacts of MSCs on mitochondrial morphology and function in host tissues. Employing in vitro cell culture of inherited mitochondrial disease and an in vivo animal experimental model of low-grade inflammation (high fat feeding), we show human-derived MSCs to alter mitochondrial function. MSC co-culture with skin fibroblasts from mitochondrial disease patients rescued aberrant mitochondrial morphology from a fission state to a more fused appearance indicating an effect of MSC co-culture on host cell mitochondrial network formation. In vivo experiments confirmed mitochondrial abundance and mitochondrial oxygen consumption rates were elevated in host tissues following MSC treatment. Furthermore, microarray profiling identified 226 genes with differential expression in the liver of animals treated with MSC, with cellular signaling, and actin cytoskeleton regulation as key upregulated processes. Collectively, our data indicate that MSC therapy rescues impaired mitochondrial morphology, enhances host metabolic capacity, and induces widespread host gene shifting. These results highlight the potential of MSCs to modulate mitochondria in both inherited and pathological disease states

Mitochondrial Stress Engages E2F1 Apoptotic Signaling to Cause Deafness

SummaryMitochondrial dysfunction causes poorly understood tissue-specific pathology stemming from primary defects in respiration, coupled with altered reactive oxygen species (ROS), metabolic signaling, and apoptosis. The A1555G mtDNA mutation that causes maternally inherited deafness disrupts mitochondrial ribosome function, in part, via increased methylation of the mitochondrial 12S rRNA by the methyltransferase mtTFB1. In patient-derived A1555G cells, we show that 12S rRNA hypermethylation causes ROS-dependent activation of AMP kinase and the proapoptotic nuclear transcription factor E2F1. This retrograde mitochondrial-stress relay is operative in vivo, as transgenic-mtTFB1 mice exhibit enhanced 12S rRNA methylation in multiple tissues, increased E2F1 and apoptosis in the stria vascularis and spiral ganglion neurons of the inner ear, and progressive E2F1-dependent hearing loss. This mouse mitochondrial disease model provides a robust platform for deciphering the complex tissue specificity of human mitochondrial-based disorders, as well as the precise pathogenic mechanism of maternally inherited deafness and its exacerbation by environmental factors.PaperFlic

Ancient mtDNA Genetic Variants Modulate mtDNA Transcription and Replication

Although the functional consequences of mitochondrial DNA (mtDNA) genetic backgrounds (haplotypes, haplogroups) have been demonstrated by both disease association studies and cell culture experiments, it is not clear which of the mutations within the haplogroup carry functional implications and which are “evolutionary silent hitchhikers”. We set forth to study the functionality of haplogroup-defining mutations within the mtDNA transcription/replication regulatory region by in vitro transcription, hypothesizing that haplogroup-defining mutations occurring within regulatory motifs of mtDNA could affect these processes. We thus screened >2500 complete human mtDNAs representing all major populations worldwide for natural variation in experimentally established protein binding sites and regulatory regions comprising a total of 241 bp in each mtDNA. Our screen revealed 77/241 sites showing point mutations that could be divided into non-fixed (57/77, 74%) and haplogroup/sub-haplogroup-defining changes (i.e., population fixed changes, 20/77, 26%). The variant defining Caucasian haplogroup J (C295T) increased the binding of TFAM (Electro Mobility Shift Assay) and the capacity of in vitro L-strand transcription, especially of a shorter transcript that maps immediately upstream of conserved sequence block 1 (CSB1), a region associated with RNA priming of mtDNA replication. Consistent with this finding, cybrids (i.e., cells sharing the same nuclear genetic background but differing in their mtDNA backgrounds) harboring haplogroup J mtDNA had a >2 fold increase in mtDNA copy number, as compared to cybrids containing haplogroup H, with no apparent differences in steady state levels of mtDNA-encoded transcripts. Hence, a haplogroup J regulatory region mutation affects mtDNA replication or stability, which may partially account for the phenotypic impact of this haplogroup. Our analysis thus demonstrates, for the first time, the functional impact of particular mtDNA haplogroup-defining control region mutations, paving the path towards assessing the functionality of both fixed and un-fixed genetic variants in the mitochondrial genome

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost