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Non-lethal genotyping of Tribolium castaneum adults using genomic DNA extracted from wing tissue
(2017)
The red flour beetle Tribolium castaneum has become the second most important insect model organism and is frequently used in developmental biology, genetics and pest-associated research. Consequently, the methodological arsenal increases continuously, but many routinely applied techniques for Drosophila melanogaster and other insect species are still unavailable. For example, a protocol for non-lethal genotyping has not yet been adapted but is particularly useful when individuals with known genotypes are required for downstream experiments. In this study, we present a workflow for non-lethal genotyping of T. castaneum adults based on extracting genomic DNA from wing tissue. In detail, we describe a convenient procedure for wing dissection and a custom method for wing digestion that allows PCR-based genotyping of up to fifty adults in less than an afternoon with a success rate of about 86%. The amount of template is sufficient for up to ten reactions while viability and fertility of the beetles are preserved. We prove the applicability of our protocol by genotyping the white / scarlet gene pair alleles from the black-eyed San Bernadino wild-type and white-eyed Pearl recessive mutant strains spanning four generations. Non-lethal genotyping has the potential to improve and accelerate many workflows: Firstly, during the establishment process of homozygous cultures or during stock keeping of cultures that carry recessively lethal alleles, laborious test crossing is replaced by non-lethal genotyping. Secondly, in genome engineering assays, non-lethal genotyping allows the identification of appropriate founders before they are crossed against wild-types, narrowing the efforts down to only the relevant individuals. Thirdly, non-lethal genotyping simplifies experimental strategies, in which genotype and behavior should be correlated, since the genetic configuration of potential individuals can be determined before the actual behavior assays is performed.
In mammals, acoustic communication plays an important role during social behaviors. Despite their ethological relevance, the mechanisms by which the auditory cortex represents different communication call properties remain elusive. Recent studies have pointed out that communication-sound encoding could be based on discharge patterns of neuronal populations. Following this idea, we investigated whether the activity of local neuronal networks, such as those occurring within individual cortical columns, is sufficient for distinguishing between sounds that differed in their spectro-temporal properties. To accomplish this aim, we analyzed simple pure-tone and complex communication call elicited multi-unit activity (MUA) as well as local field potentials (LFP), and current source density (CSD) waveforms at the single-layer and columnar level from the primary auditory cortex of anesthetized Mongolian gerbils. Multi-dimensional scaling analysis was used to evaluate the degree of “call-specificity” in the evoked activity. The results showed that whole laminar profiles segregated 1.8-2.6 times better across calls than single-layer activity. Also, laminar LFP and CSD profiles segregated better than MUA profiles. Significant differences between CSD profiles evoked by different sounds were more pronounced at mid and late latencies in the granular and infragranular layers and these differences were based on the absence and/or presence of current sinks and on sink timing. The stimulus-specific activity patterns observed within cortical columns suggests that the joint activity of local cortical populations (as local as single columns) could indeed be important for encoding sounds that differ in their acoustic attributes.
Background: Butanol isomers are regarded as more suitable fuel substitutes than bioethanol. n-Butanol is naturally produced by some Clostridia species, but due to inherent problems with clostridial fermentations, industrially more relevant organisms have been genetically engineered for n-butanol production. Although the yeast Saccharomyces cerevisiae holds significant advantages in terms of scalable industrial fermentation, n-butanol yields and titers obtained so far are only low.
Results: Here we report a thorough analysis and significant improvements of n-butanol production from glucose with yeast via the acetoacetyl-CoA-derived pathway. First, we established an improved n-butanol pathway by testing various isoenzymes of different pathway reactions. This resulted in n-butanol titers around 15 mg/L in synthetic medium after 74 h. As the initial substrate of the n-butanol pathway is acetyl-coenzyme A (acetyl-CoA) and most intermediates are bound to coenzyme A (CoA), we increased CoA synthesis by overexpression of the pantothenate kinase coaA gene from Escherichia coli. Supplementation with pantothenate increased n-butanol production up to 34 mg/L. Additional reduction of ethanol formation by deletion of alcohol dehydrogenase genes ADH1-5 led to n-butanol titers of 71 mg/L. Further expression of a mutant form of an ATP independent acetylating acetaldehyde dehydrogenase, adhEA267T/E568K, converting acetaldehyde into acetyl-CoA, resulted in 95 mg/L n-butanol. In the final strain, the n-butanol pathway genes, coaA and adhE A267T/E568K, were stably integrated into the yeast genome, thereby deleting another alcohol dehydrogenase gene, ADH6, and GPD2-encoding glycerol-3-phosphate dehydrogenase. This led to a further decrease in ethanol and glycerol by-product formation and elevated redox power in the form of NADH. With the addition of pantothenate, this strain produced n-butanol up to a titer of 130 ± 20 mg/L and a yield of 0.012 g/g glucose. These are the highest values reported so far for S. cerevisiae in synthetic medium via an acetoacetyl-CoA-derived n-butanol pathway.
Conclusions: By gradually increasing substrate supply and redox power in the form of CoA, acetyl-CoA, and NADH, and decreasing ethanol and glycerol formation, we could stepwise increase n-butanol production in S. cerevisiae. However, still further bottlenecks in the n-butanol pathway must be deciphered and improved for industrially relevant n-butanol production levels.
The genome of S. cerevisae encodes at least twenty hexose transporter-like proteins. Despite extensive research, the functions of Hxt8-Hxt17 have remained poorly defined. Here, we show that Hxt13, Hxt15, Hxt16 and Hxt17 transport two major hexitols in nature, mannitol and sorbitol, with moderate affinities, by a facilitative mechanism. Moreover, Hxt11 and Hxt15 are capable of transporting xylitol, a five-carbon polyol derived from xylose, the most abundant pentose in lignocellulosic biomass. Hxt11, Hxt13, Hxt15, Hxt16 and Hxt17 are phylogenetically and functionally distinct from known polyol transporters. Based on docking of polyols to homology models of transporters, we propose the architecture of their active site. In addition, we determined the kinetic parameters of mannitol and sorbitol dehydrogenases encoded in the yeast genome, showing that they discriminate between mannitol and sorbitol to a much higher degree than the transporters.
The amyloid precursor protein (APP) was discovered in the 1980s as the precursor protein of the amyloid A4 peptide. The amyloid A4 peptide, also known as A-beta (Aβ), is the main constituent of senile plaques implicated in Alzheimer’s disease (AD). In association with the amyloid deposits, increasing impairments in learning and memory as well as the degeneration of neurons especially in the hippocampus formation are hallmarks of the pathogenesis of AD. Within the last decades much effort has been expended into understanding the pathogenesis of AD. However, little is known about the physiological role of APP within the central nervous system (CNS). Allocating APP to the proteome of the highly dynamic presynaptic active zone (PAZ) identified APP as a novel player within this neuronal communication and signaling network. The analysis of the hippocampal PAZ proteome derived from APP-mutant mice demonstrates that APP is tightly embedded in the underlying protein network. Strikingly, APP deletion accounts for major dysregulation within the PAZ proteome network. Ca2+-homeostasis, neurotransmitter release and mitochondrial function are affected and resemble the outcome during the pathogenesis of AD. The observed changes in protein abundance that occur in the absence of APP as well as in AD suggest that APP is a structural and functional regulator within the hippocampal PAZ proteome. Within this review article, we intend to introduce APP as an important player within the hippocampal PAZ proteome and to outline the impact of APP deletion on individual PAZ proteome subcommunities.
It is long known that Kasugamycin inhibits translation of canonical transcripts containing a 5’-UTR with a Shine Dalgarno (SD) motif, but not that of leaderless transcripts. To gain a global overview of the influence of Kasugamycin on translation efficiencies, the changes of the translatome of Escherichia coli induced by a 10 minutes Kasugamycin treatment were quantified. The effect of Kasugamycin differed widely, 102 transcripts were at least twofold more sensitive to Kasugamycin than average, and 137 transcripts were at least twofold more resistant, and there was a more than 100-fold difference between the most resistant and the most sensitive transcript. The 5’-ends of 19 transcripts were determined from treated and untreated cultures, but Kasugamycin resistance did neither correlate with the presence or absence of a SD motif, nor with differences in 5’-UTR lengths or GC content. RNA Structure Logos were generated for the 102 Kasugamycin-sensitive and for the 137 resistant transcripts. For both groups a short Shine Dalgarno (SD) motif was retrieved, but no specific motifs associated with resistance or sensitivity could be found. Notably, this was also true for the region -3 to -1 upstream of the start codon and the presence of an extended SD motif, which had been proposed to result in Kasugamycin resistance. Comparison of the translatome results with the database RegulonDB showed that the transcript with the highest resistance was leaderless, but no further leaderless transcripts were among the resistant transcripts. Unexpectedly, it was found that translational coupling might be a novel feature that is associated with Kasugamycin resistance. Taken together, Kasugamycin has a profound effect on translational efficiencies of E. coli transcripts, but the mechanism of action is different than previously described.
Background: n-Butanol can serve as an excellent gasoline substitute. Naturally, it is produced by some Clostridia species which, however, exhibit only limited suitability for industrial n-butanol production. The yeast Saccharomyces cerevisiae would be an ideal host due to its high robustness in fermentation processes. Nevertheless, n-butanol yields and titers obtained so far with genetically engineered yeast strains are only low.
Results: In our recent work, we showed that n-butanol production via a clostridial acetoacetyl-CoA-derived pathway in engineered yeast was limited by the availability of coenzyme A (CoA) and cytosolic acetyl-CoA. Increasing their levels resulted in a strain producing up to 130 mg/L n-butanol under anaerobic conditions. Here, we show that under aerobic conditions. this strain can even produce up to 235 mg/L n-butanol probably due to a more efficient NADH re-oxidation. Nevertheless, expression of a bacterial water-forming NADH oxidase (nox) significantly reduced n-butanol production although it showed a positive effect on growth and glucose consumption. Screening for an improved version of an acetyl-CoA forming NAD+-dependent acetylating acetaldehyde dehydrogenase, adhEA267T/E568K/R577S, and its integration into n-butanol-producing strain further improved n-butanol production. Moreover, deletion of the competing NADP+-dependent acetaldehyde dehydrogenase Ald6 had a superior effect on n-butanol formation. To increase the endogenous supply of CoA, amine oxidase Fms1 was overexpressed together with pantothenate kinase coaA from Escherichia coli, and could completely compensate the beneficial effect on n-butanol synthesis of addition of pantothenate to the medium. By overexpression of each of the enzymes of n-butanol pathway in the n-butanol-producing yeast strain, it turned out that trans-2-enoyl-CoA reductase (ter) was limiting n-butanol production. Additional overexpression of ter finally resulted in a yeast strain producing n-butanol up to a titer of 0.86 g/L and a yield of 0.071 g/g glucose.
Conclusions: By further optimizing substrate supply and redox power in the form of coenzyme A, acetyl-CoA and NADH, n-butanol production with engineered yeast cells could be improved to levels never reached before with S. cerevisiae via an acetoacetyl-CoA-derived pathway in synthetic medium. Moreover, our results indicate that the NAD+/NADH redox balance and the trans-2-enoyl-CoA reductase reaction seem to be bottlenecks for n-butanol production with yeast.
Maintenance of mitochondria is achieved by several mechanisms, including the regulation of mitochondrial proteostasis. The matrix protease CLPXP, involved in protein quality control, has been implicated in ageing and disease. However, particularly due to the lack of knowledge of CLPXP's substrate spectrum, only little is known about the pathways and mechanisms controlled by this protease. Here we report the first comprehensive identification of potential mitochondrial CLPXP in vivo interaction partners and substrates using a combination of tandem affinity purification and differential proteomics. This analysis reveals that CLPXP in the fungal ageing model Podospora anserina is mainly associated with metabolic pathways in mitochondria, e.g. components of the pyruvate dehydrogenase complex and the tricarboxylic acid cycle as well as subunits of electron transport chain complex I. These data suggest a possible function of mitochondrial CLPXP in the control and/or maintenance of energy metabolism. Since bioenergetic alterations are a common feature of neurodegenerative diseases, cancer, and ageing, our data comprise an important resource for specific studies addressing the role of CLPXP in these adverse processes.
Abstract: The hallmarks of Alzheimer’s disease (AD) are characterized by cognitive decline and behavioral changes. The most prominent brain region affected by the progression of AD is the hippocampal formation. The pathogenesis involves a successive loss of hippocampal neurons accompanied by a decline in learning and memory consolidation mainly attributed to an accumulation of senile plaques. The amyloid precursor protein (APP) has been identified as precursor of Aβ-peptides, the main constituents of senile plaques. Until now, little is known about the physiological function of APP within the central nervous system. The allocation of APP to the proteome of the highly dynamic presynaptic active zone (PAZ) highlights APP as a yet unknown player in neuronal communication and signaling. In this study, we analyze the impact of APP deletion on the hippocampal PAZ proteome. The native hippocampal PAZ derived from APP mouse mutants (APP-KOs and NexCreAPP/APLP2-cDKOs) was isolated by subcellular fractionation and immunopurification. Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry. We combine bioinformatics tools and biochemical approaches to address the proteomics dataset and to understand the role of individual proteins. The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis. The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.
Author Summary: More than 20 years ago, the amyloid precursor protein (APP) was identified as the precursor protein of the Aβ peptide, the main component of senile plaques in brains affected by Alzheimer’s disease. However, little is known about the physiological function of amyloid precursor protein. Allocating APP to the proteome of the structurally and functionally dynamic presynaptic active zone highlights APP as a hitherto unknown player within the presynaptic network. The hippocampus is the most prominent brain region for learning and memory consolidation, and a vulnerable target for neurodegenerative disease, e. g. Alzheimer’s disease. Therefore, our experimental design is focused on the hippocampal neurotransmitter release site. Currently, the underlying mechanism of how APP acts within presynaptic networks is still elusive. Within the scope of this research article, we constructed a network of APP within the presynaptic active zone and how deletion of APP affects these individual networks. We combine bioinformatics tools and biochemical approaches to address the dataset provided by proteomics. Furthermore, we could unravel that APP executes regulatory functions within the synaptic vesicle cycle, cytoskeletal rearrangements and Ca2+-homeostasis. Taken together, our findings offer a new perspective on the physiological function of APP in the central nervous system and may provide a molecular link to the pathogenesis of Alzheimer’s disease.
Background: Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset.
Results: We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values.
Conclusion: We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.