Cellular fatty acids of Helicobacter pylori have taxonomic, physiological, and pathogenic implications. However, little is known about the fatty acid composition under various culture conditions. H. pylori is usually grown on blood-supplemented complex media, and the fatty acids in the blood may affect the fatty acids in the cells. In addition, frequently subcultivated laboratory-adapted strains may have properties different from those of fresh clinical isolates, which are culturable only for a limited number of passages. Therefore, the cellular fatty acid profiles of laboratory-adapted strains (LAS) and freshly isolated strains (FIS) were compared after growth on agar that was fatty acid free and growth on blood agar that contained fatty acids. LAS ATCC 43504, 51932, and 700392 and the FIS IMMi 88, 89, and 92, each with <10 subcultures, were cultured in parallel on a fatty acid-free agar (ISAF) and on 5% sheep blood agar (SBA), which contained oleic acid (18:1 9c), hexadecanoic acid (16:0), and octadecanoic acid (18:0). ISAF-grown cultures showed no 18:1 9c and no appreciable differences between the profiles of FIS and LAS. After culture on SBA, the strains showed 18:1 9c and increased 16:0 and 18:0 content combined with decreased tetradecanoic acid (14:0) content compared to ISAF-grown cells. The changes in the fatty acid profiles were much more pronounced in FIS than in LAS. LAS are obviously characterized by a lower uptake of the fatty acids from the growth medium than FIS. Furthermore, it could be shown that this LAS behavior is most likely a primary strain attribute that is favored under laboratory conditions. The pronounced uptake of fatty acids by strains with FIS behavior may be associated with the expression of virulence properties.Helicobacter pylori exhibits a unique profile of cellular fatty acids which is markedly different from that of other enteropathogenic gram-negative bacteria (4-7, 11, 21). Tetradecanoic acid (14:0) and methyleneoctadecanoic acid (19:0 cyclo) are major fatty acids, whereas hexadecanoic acid (16:0) is represented in relatively small amounts, and hexadecenoic acid (16:1) cannot be detected at all (4-7, 11, 15). One property that is unusual but characteristic is the fatty acid distribution among the different lipid classes. The phospholipids are predominantly substituted with 14:0 and 19:0 cyclo fatty acids, whereas ␤-hydroxy or unsaturated fatty acids can only be detected, if at all, in small amounts, which may account for unusual membrane properties (4, 15, 18). The lipopolysaccharide (LPS) of H. pylori is predominantly different from those of other bacteria and has octadecanoic acid (18:0) and longer-chain 3-hydroxy fatty acids, like 3-hydroxy-hexadecanoic acid (3-OH 16:0) and 3-hydroxy-octadecanoic acid (3-OH 18:0), which may explain the low endotoxic and biological activities of H. pylori LPS (4, 13-15). Thus, the fatty acid substitution of H. pylori lipids may have physiological and pathogenic implications.It is well known that environmental and physiological factors affec...

Genomic surveillance of the SARS-CoV-2 pandemic is crucial and mainly achieved by amplicon sequencing protocols. Overlapping tiled-amplicons are generated to establish contiguous SARS-CoV-2 genome sequences, which enable the precise resolution of infection chains and outbreaks. We investigated a SARS-CoV-2 outbreak in a local hospital and used nanopore sequencing with a modified ARTIC protocol employing 1200 bp long amplicons. We detected a long deletion of 168 nucleotides in the ORF8 gene in 76 samples from the hospital outbreak. This deletion is difficult to identify with the classical amplicon sequencing procedures since it removes two amplicon primer-binding sites. We analyzed public SARS-CoV-2 sequences and sequencing read data from ENA and identified the same deletion in over 100 genomes belonging to different lineages of SARS-CoV-2, pointing to a mutation hotspot or to positive selection. In almost all cases, the deletion was not represented in the virus genome sequence after consensus building. Additionally, further database searches point to other deletions in the ORF8 coding region that have never been reported by the standard data analysis pipelines. These findings and the fact that ORF8 is especially prone to deletions, make a clear case for the urgent necessity of public availability of the raw data for this and other large deletions that might change the physiology of the virus towards endemism.

As COVID-19 has spread from the first reported cases into a global pandemic, there has been a number of efforts to understand the mutations and clusters of genetic lineages of the SARS-CoV-2 virus. The high mutation rate and rapid spread makes this analysis capable of tracking chains of infections as well as putting individual sequences in context. Whole genomes of the SARS-CoV-2 virus are being collected and shared from across the globe. With the advent of affordable and prolific Next Generation Sequencing, this is the first pandemic in which the genomic evolution of the pathogen can be tracked in near real-time. So far, phylogenetic analysis methods have recently found a broader application in this regard. Here we demonstrate that Principal Component Analysis (PCA), used heavily in population genetics, corroborates the existing findings while providing unique new capabilities to understand our public repositories of complete virus sequences. This novel application of PCA is demonstrated on all publicly available SARS-CoV-2 samples from GenBank and other open-access databases until mid-April. We show that PCA is a useful and easy-to-use tool to analyze SARS-CoV-2 genomes in addition to phylogenetic analytics. It offers a previously untapped opportunity to analyze the dynamics of the current SARS-CoV-2 pandemic in a new way.

Since the beginning of the global SARS-CoV-2 pandemic, there have been a number of efforts to understand the mutations and clusters of genetic lines of the SARS-CoV-2 virus. Until now, phylogenetic analysis methods have been used for this purpose. Here we show that Principal Component Analysis (PCA), which is widely used in population genetics, can not only help us to understand existing findings about the mutation processes of the virus, but can also provide even deeper insights into these processes while being less sensitive to sequencing gaps. Here we describe a comprehensive analysis of a 46,046 SARS-CoV-2 genome sequence dataset downloaded from the GISAID database in June of this year.SummaryPCA provides deep insights into the analysis of large data sets of SARS-CoV-2 genomes, revealing virus lineages that have thus far been unnoticed.