CRISPR/Cas9 gene targeting plus nanopore DNA sequencing with the plasmid pBR322 in the classroom.

Both nanopore-based DNA sequencing and CRISPR/Cas-based gene editing represent groundbreaking innovations in molecular biology and genomics, offering unprecedented insights into and tools for working with genetic information. For students, reading, editing, and even writing DNA will be part of their everyday life. We have developed a laboratory procedure that includes (i) the biosynthesis of a guide RNA for, (ii) targeting Cas9 to specifically linearize the pBR322 plasmid, and (iii) the identification of the cutting site through nanopore DNA sequencing. The protocol is intentionally kept simple and requires neither living organisms nor biosafety laboratories. We divided the experimental procedures into separate activities to facilitate customization. Assuming access to a well-equipped molecular biology laboratory, an initial investment of approximately $2,700 is necessary. The material costs for each experiment group amount to around $130. Furthermore, we have developed a freely accessible website (https://dnalesen.hs-mittweida.de) for sequence read analysis and visualization, lowering the required computational skills to a minimum. For those with strong computational skills, we provide instructions for terminal-based data processing. With the presented activities, we aim to provide a hands-on experiment that engages students in modern molecular genetics and motivates them to discuss potential implications. The complete experiment can be accomplished within half a day and has been successfully implemented by us at high schools, in teacher training, and at universities. Our tip is to combine CRISPR/Cas gene targeting with nanopore-based DNA sequencing. As a tool, we provide a website that facilitates sequence data analysis and visualization.

Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures.

BACKGROUND: We benchmarked sequencing technology and assembly strategies for short-read, long-read, and hybrid assemblers in respect to correctness, contiguity, and completeness of assemblies in genomes of Francisella tularensis. Benchmarking allowed in-depth analyses of genomic structures of the Francisella pathogenicity islands and insertion sequences. Five major high-throughput sequencing technologies were applied, including next-generation "short-read" and third-generation "long-read" sequencing methods. RESULTS: We focused on short-read assemblers, hybrid assemblers, and analysis of the genomic structure with particular emphasis on insertion sequences and the Francisella pathogenicity island. The A5-miseq pipeline performed best for MiSeq data, Mira for Ion Torrent data, and ABySS for HiSeq data from eight short-read assembly methods. Two approaches were applied to benchmark long-read and hybrid assembly strategies: long-read-first assembly followed by correction with short reads (Canu/Pilon, Flye/Pilon) and short-read-first assembly along with scaffolding based on long reads (Unicyler, SPAdes). Hybrid assembly can resolve large repetitive regions best with a "long-read first" approach. CONCLUSIONS: Genomic structures of the Francisella pathogenicity islands frequently showed misassembly. Insertion sequences (IS) could be used to perform an evolutionary conservation analysis. A phylogenetic structure of insertion sequences and the evolution within the clades elucidated the clade structure of the highly conservative F. tularensis.

Using ITS2 metabarcoding and microscopy to analyse shifts in pollen diets of honey bees and bumble bees along a mass-flowering crop gradient.

Worldwide pollinator declines lead to pollination deficits in crops and wild plants, and managed bees are frequently used to meet the increasing demand for pollination. However, their foraging can be affected by flower availability and colony size. We investigated how mass-flowering oilseed rape (OSR) can influence the pollen resource use of small and large honey bee (Apis mellifera L.) and bumble bee (Bombus terrestris L.) colonies. Colonies were placed adjacent to strawberry fields along a gradient of OSR availability in the landscapes. We used ITS2 metabarcoding to identify the pollen richness based on ITS2 amplicon sequencing and microscopy for quantification of target pollen. Bumble bees collected pollen from more different plant genera than honey bees. In both species, strawberry pollen collection decreased with high OSR availability but was facilitated by increasing strawberry flower cover. Colony size had no effect. The relationship between next-generation sequencing-generated ITS2 amplicon reads and microscopic pollen counts was positive but pollen type-specific. Bumble bees and, to a lesser degree, honey bees collected pollen from a wide variety of plants. Therefore, in order to support pollinators and associated pollination services, future conservation schemes should sustain and promote pollen plant richness in agricultural landscapes. Both bee species responded to the availability of flower resources in the landscape. Although honey bees collected slightly more strawberry pollen than bumble bees, both can be considered as crop pollinators. Metabarcoding could provide similar quantitative information to microscopy, taking into account the pollen types, but there remains high potential to improve the methodological weaknesses.

Draft Genome Assembly of Rhodobacter sphaeroides 2.4.1 Substrain H2 from Nanopore Data.

Rhodobacter sphaeroides is a purple bacterium with complex genomic architecture. Here, a draft genome is reported for R. sphaeroides strain 2.4.1 substrain H2, which was generated exclusively from Nanopore sequencing data.

Analyzing the Dietary Diary of Bumble Bee.

Bumble bees are important crop pollinators and provide important pollination services to their respective ecosystems. Their pollen diet and thus food preferences can be characterized through nucleic acid sequence analysis. We present ITS2 amplicon sequence data from pollen collected by bumble bees. The pollen was collected from six different bumble bee colonies that were placed in independent agricultural landscapes. We compared next-generation (Illumina), i.e., short-read, and third-generation (Nanopore), i.e., MinION, sequencing techniques. MinION data were preprocessed using traditional and Nanopore specific tools for comparative analysis and were evaluated in comparison to short-read sequence data with conventional processing. Based on the results, the dietary diary of bumble bee in the studied landscapes can be identified. It is known that short reads generated by next-generation sequencers have the advantage of higher quality scores while Nanopore yields longer read lengths. We show that assignments to taxonomic units yield comparable results when querying against an ITS2-specific sequence database. Thus, lower sequence quality is compensated by longer read lengths. However, the Nanopore technology is improving in terms of data quality, much cheaper, and suitable for portable applications. With respect to the studied agricultural landscapes we found that bumble bees require higher plant diversity than only crops to fulfill their foraging requirements.

Benchmarking the MinION: Evaluating long reads for microbial profiling.

Nanopore based DNA-sequencing delivers long reads, thereby simplifying the decipherment of bacterial communities. Since its commercial appearance, this technology has been assigned several attributes, such as its error proneness, comparatively low cost, ease-of-use, and, most notably, aforementioned long reads. The technology as a whole is under continued development. As such, benchmarks are required to conceive, test and improve analysis protocols, including those related to the understanding of the composition of microbial communities. Here we present a dataset composed of twelve different prokaryotic species split into four samples differing by nucleic acid quantification technique to assess the specificity and sensitivity of the MinION nanopore sequencer in a blind study design. Taxonomic classification was performed by standard taxonomic sequence classification tools, namely Kraken, Kraken2 and Centrifuge directly on reads. This allowed taxonomic assignments of up to 99.27% on genus level and 92.78% on species level, enabling true-positive classification of strains down to 25,000 genomes per sample. Full genomic coverage is achieved for strains abundant as low as 250,000 genomes per sample under our experimental settings. In summary, we present an evaluation of nanopore sequence processing analysis with respect to microbial community composition. It provides an open protocol and the data may serve as basis for the development and benchmarking of future data processing pipelines.

SDS-PAGE fractionation to increase metaproteomic insight into the taxonomic and functional composition of microbial communities for biogas plant samples.

Metaproteomics represent an important tool for the taxonomic and functional investigation of microbial communities in humans, environment, and technical applications. Due to the high complexity of the microbial communities, protein, and peptide fractionation is applied to improve the characterization of taxonomic and functional composition of microbial communities. In order to target scientific questions regarding taxonomic and functional composition adequately, a tradeoff between the number of fractions analyzed and the required depth of information has to be found. Two samples of a biogas plant were analyzed by either single LC-MS/MS measurement (1D) or LC-MS/MS measurements of fractions obtained after SDS-PAGE (2D) separation. Fractionation with SDS-PAGE increased the number of identified spectra by 273%, the number of peptides by 95%, and the number of metaproteins by 59%. Rarefaction plots of species and metaproteins against identified spectra showed that 2D separation was sufficient to identify most microbial families but not all metaproteins. More reliable quantitative comparison could be achieved with 2D. 1D separation enabled high-throughput analysis of samples, however, depth in functional descriptions and reliability of quantification were lost. Nevertheless, the proteotyping of multiple samples was still possible. 2D separations provided more reliable quantitative data combined with a deeper insight into the taxonomic and functional composition of the microbial communities. Regarding taxonomic and functional composition, metaproteomics based on 2D is just the tip of an iceberg.

Efficiency of RNA extraction from selected bacteria in the context of biogas production and metatranscriptomics.

Understanding the microbial population in anaerobic digestion is an essential task to increase efficient substrate use and process stability. The metabolic state, represented e.g. by the transcriptome, of a fermenting system can help to find markers for monitoring industrial biogas production to prevent failures or to model the whole process. Advances in next-generation sequencing make transcriptomes accessible for large-scale analyses. In order to analyze the metatranscriptome of a mixed-species sample, isolation of high-quality RNA is the first step. However, different extraction methods may yield different efficiencies in different species. Especially in mixed-species environmental samples, unbiased isolation of transcripts is important for meaningful conclusions. We applied five different RNA-extraction protocols to nine taxonomic diverse bacterial species. Chosen methods are based on various lysis and extraction principles. We found that the extraction efficiency of different methods depends strongly on the target organism. RNA isolation of gram-positive bacteria was characterized by low yield whilst from gram-negative species higher concentrations can be obtained. Transferring our results to mixed-species investigations, such as metatranscriptomics with biofilms or biogas plants, leads to the conclusion that particular microorganisms might be over- or underrepresented depending on the method applied. Special care must be taken when using such metatranscriptomics data for, e.g. process modeling.

Nutrilyzer: a tool for deciphering atomic stoichiometry of differentially expressed paralogous proteins.

Organisms try to maintain homeostasis by balanced uptake of nutrients from their environment. From an atomic perspective this means that, for example, carbon:nitrogen:sulfur ratios are kept within given limits. Upon limitation of, for example, sulfur, its acquisition is triggered. For yeast it was shown that transporters and enzymes involved in sulfur uptake are encoded as paralogous genes that express different isoforms. Sulfur deprivation leads to up-regulation of isoforms that are poor in sulfur-containing amino acids, that is, methinone and cysteine. Accordingly, sulfur-rich isoforms are down-regulated. We developed a web-based software, doped Nutrilyzer, that extracts paralogous protein coding sequences from an annotated genome sequence and evaluates their atomic composition. When fed with gene-expression data for nutrient limited and normal conditions, Nutrilyzer provides a list of genes that are significantly differently expressed and simultaneously contain significantly different amounts of the limited nutrient in their atomic composition. Its intended use is in the field of ecological stoichiometry. Nutrilyzer is available at http://nutrilyzer.hs-mittweida.de. Here we describe the work flow and results with an example from a whole-genome Arabidopsis thaliana gene-expression analysis upon oxygen deprivation. 43 paralogs distributed over 37 homology clusters were found to be significantly differently expressed while containing significantly different amounts of oxygen.

MAVisto: a tool for biological network motif analysis.

Data from high-throughput experimental methods are currently being used to construct complex biological networks. These include regulatory gene networks, regulatory protein-DNA networks, protein-protein interaction networks, or metabolic networks. Independent of its type, every network can be characterized by a number of parameters such as number of nodes, number of edges connecting nodes, direction and weight of edges, in- and out-degree of nodes, etc. One can draw an analogy of such rather simple network parameters to the primary sequence of proteins or nucleic acids. More insight can be gained by an analysis of the secondary and tertiary structure of biomolecules, which often contain motifs. The same holds for biological networks. The occurrence and frequency of certain motifs or pattern characterize the topology and often the functional space of a network. Here, we describe the utilization of the free software MAVisto, which was designed to mine networks for typical motifs by combining a flexible motif search algorithm with interactive exploration methods and sophisticated visualization techniques.

The LAILAPS search engine: relevance ranking in life science databases.

Search engines and retrieval systems are popular tools at a life science desktop. The manual inspection of hundreds of database entries, that reflect a life science concept or fact, is a time intensive daily work. Hereby, not the number of query results matters, but the relevance does. In this paper, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. With a set of features, extracted from each database hit in combination with user relevance preferences, a neural network predicts user specific relevance scores. Using expert knowledge as training data for a predefined neural network or using users own relevance training sets, a reliable relevance ranking of database hits has been implemented. In this paper, we present the LAILAPS system, the concepts, benchmarks and use cases. LAILAPS is public available for SWISSPROT data at http://lailaps.ipk-gatersleben.de.

Experimental and bioinformatic approaches for analyzing and visualizing cyanobacterial nitrogen and hydrogen metabolism

Many cyanobacteria are capable of utilizing light energy for nitrogen fixation. As a by-product of this nitrogenase mediated catalysis, hydrogen gas is produced. Several approaches to increase hydrogen production from cyanobacteria exist. Usually, these approaches are non-targeted. Here we exemplify how DNA-microarray based gene-expression analysis and bioinformatic visualization techniques can be used to analyze nitrogen and hydrogen metabolism from the filamentous, heterocyst forming cyanobacterium Nostoc PCC 7120. We analyzed the expression of 1249 genes from major metabolic categories under nitrogen fixing and non-nitrogen fixing growth. Of the selected genes, 494 show a more than 2-fold expression difference in the two conditions analyzed. Under nitrogen-fixing conditions 465 genes, mainly involved in energy metabolism, photosynthesis, respiration and nitrogen-fixation, were found to be stronger expressed, whereas only 29 genes showed a stronger expression under non-nitrogen fixing conditions. To help understanding probe hybridization, all expression data were correlated with potential target secondary structures and probe GC-content. For the first time the expression of high light-induced stress proteins (HLIP-family) is shown to be linked to the nitrogen availability.

Presence and expression of hydrogenase specific C-terminal endopeptidases in cyanobacteria.

BACKGROUND: Hydrogenases catalyze the simplest of all chemical reactions: the reduction of protons to molecular hydrogen or vice versa. Cyanobacteria can express an uptake, a bidirectional or both NiFe-hydrogenases. Maturation of those depends on accessory proteins encoded by hyp-genes. The last maturation step involves the cleavage of a ca. 30 amino acid long peptide from the large subunit by a C-terminal endopeptidase. Until know, nothing is known about the maturation of cyanobacterial NiFe-hydrogenases. The availability of three complete cyanobacterial genome sequences from strains with either only the uptake (Nostoc punctiforme ATCC 29133/PCC 73102), only the bidirectional (Synechocystis PCC 6803) or both NiFe-hydrogenases (Anabaena PCC 7120) prompted us to mine these genomes for hydrogenase maturation related genes. In this communication we focus on the presence and the expression of the NiFe-hydrogenases and the corresponding C-terminal endopeptidases, in the three strains mentioned above. RESULTS: We identified genes encoding putative cyanobacterial hydrogenase specific C-terminal endopeptidases in all analyzed cyanobacterial genomes. The genes are not part of any known hydrogenase related gene cluster. The derived amino acid sequences show only low similarity (28-41%) to the well-analyzed hydrogenase specific C-terminal endopeptidase HybD from Escherichia coli, the crystal structure of which is known. However, computational secondary and tertiary structure modeling revealed the presence of conserved structural patterns around the highly conserved active site. Gene expression analysis shows that the endopeptidase encoding genes are expressed under both nitrogen-fixing and non-nitrogen-fixing conditions. CONCLUSION: Anabaena PCC 7120 possesses two NiFe-hydrogenases and two hydrogenase specific C-terminal endopeptidases but only one set of hyp-genes. Thus, in contrast to the Hyp-proteins, the C-terminal endopeptidases are the only known hydrogenase maturation factors that are specific. Therefore, in accordance with previous nomenclature, we propose the gene names hoxW and hupW for the bidirectional and uptake hydrogenase processing endopeptidases, respectively. Due to their constitutive expression we expect that, at least in cyanobacteria, the endopeptidases take over multiple functions.

Hydrogenases and hydrogen metabolism of cyanobacteria.

Cyanobacteria may possess several enzymes that are directly involved in dihydrogen metabolism: nitrogenase(s) catalyzing the production of hydrogen concomitantly with the reduction of dinitrogen to ammonia, an uptake hydrogenase (encoded by hupSL) catalyzing the consumption of hydrogen produced by the nitrogenase, and a bidirectional hydrogenase (encoded by hoxFUYH) which has the capacity to both take up and produce hydrogen. This review summarizes our knowledge about cyanobacterial hydrogenases, focusing on recent progress since the first molecular information was published in 1995. It presents the molecular knowledge about cyanobacterial hupSL and hoxFUYH, their corresponding gene products, and their accessory genes before finishing with an applied aspect--the use of cyanobacteria in a biological, renewable production of the future energy carrier molecular hydrogen. In addition to scientific publications, information from three cyanobacterial genomes, the unicellular Synechocystis strain PCC 6803 and the filamentous heterocystous Anabaena strain PCC 7120 and Nostoc punctiforme (PCC 73102/ATCC 29133) is included.