MEGA SAMPLES VOL-104
Nelson Suggs
Sample pack is full of influences from traditional Balkan and Oriental music, with instruments like Lute (Greek traditional handmade stringed instrument) and Saz (Sazi in Greek).
You can find here also a collection of beats and ethnic percussions, various sounds of Clavinet V, groovy basslines from ARP Odyssey and from other synthesizers.
Organic Session vol. 2 provides orientalist Organic House / Afro House samples and ritual sounds inspired by major labels such as Sol Selectas, Cosmic Awakenings, Lump Records, Cafe De Anatolia, Exotic Refreshment, Pipe & Pochet etc.
Whole-genome sequencing has become an indispensible tool of modern biology. However, the cost of sample preparation relative to the cost of sequencing remains high, especially for small genomes where the former is dominant. Here we present a protocol for rapid and inexpensive preparation of hundreds of multiplexed genomic libraries for Illumina sequencing. By carrying out the Nextera tagmentation reaction in small volumes, replacing costly reagents with cheaper equivalents, and omitting unnecessary steps, we achieve a cost of library preparation of $8 per sample, approximately 6 times cheaper than the standard Nextera XT protocol. Furthermore, our procedure takes less than 5 hours for 96 samples. Several hundred samples can then be pooled on the same HiSeq lane via custom barcodes. Our method will be useful for re-sequencing of microbial or viral genomes, including those from evolution experiments, genetic screens, and environmental samples, as well as for other sequencing applications including large amplicon, open chromosome, artificial chromosomes, and RNA sequencing.
Samples had between 0.2 and 2.8 million reads with 90% of samples having over 1 million reads. Raw reads were filtered and then aligned to a reference genome using bowtie2. Unique reads are those that appear only once in the alignment for a particular sample. These are the reads that remain after use of the rmdup tool in samtools. Non-unique reads arise primarily when the same tagmented fragment is amplified during PCR. A low fraction of non-unique reads implies a diversity of fragments after tagmentation, and that errors introduced during PCR will not reach high frequencies.
In this module, PCR is used to incorporate the remaining Illumina adaptor sequences and sample barcodes to tagmented DNA fragments. The adaptors bind fragments to the flow cell [14], and the barcodes allow for multiplexed sequencing. If 96 or fewer samples are pooled on a single lane, we use the Illumina TruSeq primers S501-S508 and N701-N712. For higher multiplexing requirements, we developed custom row and column primers, labeled R09-R36 and C13-C24. These were derived from the TruSeq primers and are compatible with them (S1 Table). Also, Illumina now has additional TruSeq barcodes. When combining the barcodes in this paper with other sets beyond S501-S508 and N701-712, care should be taken to verify that pairs of barcodes remain at sufficiently distant Hamming distances for disambiguation (we recommend at least 3bp).
In this module, sample concentrations and fragment size distributions are estimated and libraries are pooled. We measure the DNA concentration of each sample fluorescently, as in Module 1; quantification by qPCR is unnecessary at this stage. We discard samples with less than 0.5ng of DNA. Fragment size distribution can be measured with Agilent BioAnalyzer, TapeStation, Bio-Rad Experion, or a number of other devices. While it would be ideal to measure the size distribution of every sample, this is not practical or economically feasible at large scale. Moreover, we found that sample preps from the same 96-well plate typically have similar post-cleanup fragment-size distributions. Thus, we estimate this distribution for a subset of samples (5 to 10). Then, based on individual sample concentrations and the common average fragment length, we calculate the DNA molarity of each sample and pool variable volumes of samples to achieve equimolar concentrations in the pool. Despite the fact that average fragment length can vary across a plate (Fig 5A), Plate 2), calculating molarity based on a few samples results in roughly uniform numbers of reads for 90% of samples (Fig 5B). For applications that are sensitive to fragment size (e.g. de novo assembly), modification of the tagmentation reaction ratios and size-selection cleanup (e.g. via bead-based dual purification, PippinPrep or E-Gel) may be required.
Data is from two plates of E. coli samples, with 83 and 95 samples per plate (S2 Table). Input gDNA concentrations ranged from 2 to 25ng/μl, and were standardized to 0.5ng/μl. Based on estimated fragment-length distributions, Plates 1 and 2 were pooled in mass ratio 0.8:1. In this preparation, 2 samples (1%) failed to yield libraries, and 17 (10%) produced low, but usable, numbers of reads (between 0.1 and 0.4 million)
Note: This procedure assumes gDNA concentration in the range of 1-10ng/μl. If samples cover a different range of concentrations, the procedure should be modified accordingly. We recommend a two step-dilution for samples with a broad range of concentrations.
Note: All reagents should be kept on ice. The 96-well plate containing samples should also be kept on ice while assembling the mix, and all steps should be done quickly. Small volume reactions can be difficult to work with; do not skip centrifugation.
We used CRISPR targeting12 to identify Prevotella as the megaphage host (Fig. 1 and Supplementary Fig. 3, Supplementary Information). Given that many of the individuals have gut microbiomes dominated by Prevotella, we tested for megaphages in all the Laksam Upazila microbiome samples and found evidence for them in samples from individuals 21 and 23 (Supplementary Information). We attempted to isolate the megaphages using faecal material and Prevotella copri DSM 1820513 but isolation was unsuccessful (Supplementary Information).
The green rods indicate repeats, the coloured rods indicate spacers. The same colour indicates the same spacer sequence, except for black rods, which indicate spacers different between individuals 26 and 28 (probably added to the diversifying locus ends). The red arrows indicate spacers targeting megaphages (also see Supplementary Fig. 3).
We identified a diversity of Prevotella strains via 16S ribosomal RNA (rRNA) gene phylogenetic analysis. However, we found no clear link between cohort type and Prevotella species, or Prevotella species and megaphages (Supplementary Fig. 7).
Genomes with repurposed stop codons typically encode a suppressor tRNA. Multiple types of suppressor tRNAs were predicted (Supplementary Information and Supplementary Table 2), including one with a CTA anticodon that is necessary to repurpose the TAG stop codon. All complete megaphage genomes also encode release factor 2, which terminates translation by recognizing the TGA and TAA, but not TAG, stop codons. Thus, megaphages have the cellular machinery necessary to successfully translate genes with in-frame recoded TAG.
If Prevotella and their megaphages migrate among animal and human microbiomes, they could carry with them genes that are relevant to human and animal health and the spread of disease. The concept of zoonotic viruses is well established, but there may be analogous phenomena involving phages. Phages can disseminate virulence factors between bacterial strains, including toxin-encoding genes responsible for many important diseases such as diphtheria, cholera, dysentery, botulism, food poisoning, staphylococcal scalded skin syndrome, necrotizing pneumonia or scarlet fever8,24 and propagate other genes of medical interest among animal reservoirs, such as those involved in antimicrobial resistance. The finding of related Lak phages in baboon, pig, cow and human populations suggests this possibility; the probability that it may occur is clearly increased where phages have huge genomes.
The existence of megaphages motivates the general question of the costs and benefits to the phages of large genomes and the feedbacks that drive their evolution. Lak phage genomes encode many tRNAs, which could improve their replication success (see Supplementary Information), but the span of genome-encoding tRNAs is small. More probably, the hundreds of hypothetical proteins in the genomes may ensure successful phage replication in the face of host defence mechanisms and could also be important for increasing the host range.
Evolution of large phage genomes, and thus few expensive particles per replication cycle, could be an ecological strategy analogous to K- versus r-selection. Phages would normally be viewed as r-strategists, leveraging the advantage of many offspring to ensure high probability that a particle will find a host where it can replicate before loss of viability. For large phages, the countering trade-off of a shift towards K-selection could be improved survival as the result of the large capsid size. Potentially, this is because of the increased stability of larger capsids, for example, due to their smaller radius of curvature. Clearly, many factors could come into play, and direct experiments involving isolated phages and their hosts are required to understand the intriguing phenomenon of megaphages in human and other animal gut microbiomes.
The cohort of cholera patients comprised 42 men, 3 women, and 2 male and 2 female children. These samples were previously sequenced; see Methods from David et al.4 for information regarding informed consent and sampling protocols. The original study was approved by the Ethical and Research Review Committees of the International Centre for Diarrhoeal Disease Research, Bangladesh and the Institutional Review Board of Massachusetts General Hospital.
The Prevotella phylogenetic tree was constructed using 16S rRNA gene sequences. First, the Greengenes database42 of complete 16S rRNA gene sequences was augmented with all 16S rRNA gene sequences from Prevotella reference sequences on the NCBI that were independently classified as Prevotella (15 were assigned to a genus other than Prevotella and discarded). This augmented database was then used to classify 16S rRNA gene sequences from all samples in each study where a megaphage was found, including samples in publicly available studies, using the assign_taxonomy.py script from qiime1 and default parameters43. Sequences classified as Prevotella were aligned with all known reference Prevotella 16S rRNA gene sequences and an Escherichia coli 16S rRNA gene outgroup (NCBI ref. J01859.1) using MUSCLE44. A tree was generated using RAxML-HPC2 on XSEDE45 on the CIPRES Science Gateway46 using parameters raxmlHPC-HYBRID -T 4 -n result -s infile.txt -m GTRGAMMA -p 12345 -k -f a -N 100 -x 12345 --asc-corr lewis. The tree was edited and annotated with iTOL47.
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