Infrared spectroscopy is a prominent molecular technique for bacterial analysis. Within its context, near infrared spectroscopy in particular brings benefits over other vibrational approaches; these advantages include, for example, lower sensitivity to water, high penetration depth and low cost. However, near infrared spectroscopy is not popular within microbiology, because the spectra of organic samples are difficult to interpret. We propose a comparison of spectral curve-fitting methods, namely, techniques that facilitate the interpretation of most peaks, simplify the spectra and improve the prediction of bacterial species from the relevant near infrared spectra. The performances of three common curve-fitting algorithms and the technique based on the differential evolution were compared via a synthesized experimental spectrum. Utilizing the obtained results, the spectra of three different bacterial species were curve fit by optimized algorithm. The proposed algorithm decomposed the spectra to specific absorption peaks, whose parameters were estimated via the differential evolution approach initialized through Levenberg-Marquardt optimization; subsequently, the spectra were classified with conventional procedures and using the parameters of the revealed peaks. On a limited data set, the correct classification rate computed by partial least squares discriminant analysis was 95%. When we employed the peak parameters for the classification, the rate corresponded to 91.7%. According to the Gaussian formula, the parameters comprise the spectral peak position, amplitude and width. The most important peaks for bacterial discrimination were identified by analysis of variance and interpreted as N-H stretching bonds in proteins, cis bonds and CH 2 absorption in fatty acids. We examined some aspects of the behaviour of standard curve-fitting algorithms and proposed differential evolution to optimize the fitting process. Based on the correct use of these algorithms, the near infrared spectra of bacteria can be interpreted and the full potential of near infrared spectroscopy in microbiology exploited.
In recent years, near infrared (NIR) spectroscopy has gained interest as a tool for bacteria strain identification. Although some promising results suggest good applicability of the technique, a better interpretation of the NIR bacterial spectra is still needed. In order to analyze the NIR spectrum of biological samples, a correlation analysis between the NIR and the mid-infrared (mid-IR) spectra was performed. In total, 28 spectra of 8 bacterial strains were acquired and correlated in the NIR and the mid-IR spectral ranges. Some molecular bands (Amide I, P = O stretching, C-H stretching/deformation of polysaccharides) were well correlated, and the effect of concentration changes in these molecules were investigated. Moreover, a model for the NIR spectra classification was created with an overall 85% correct classification rate. Subsequently, only NIR wavelengths with high correlation to important mid-IR peaks were selected. This led to an increase in the correct classification rate to 94%. By correlation between well-established mid-IR peaks and NIR spectra, some relationships in the NIR spectra of biological samples were revealed, which was a step towards better understanding and interpretation of the NIR spectra of biological samples.
Worldwide distributed marine alga Emiliania huxleyi produces reflective calcite disks (coccoliths) that increase the albedo of ocean water and thus reduce the heat absorption in oceans, which cools the Earth's climate. The population density of E. huxleyi is restricted by nucleocytoplasmic large DNA viruses, including E. huxleyi virus 201 (EhV-201). Despite the impact of E. huxleyi viruses on the climate, there is limited information about their structure and replication. Here we show that the dsDNA genome inside the EhV-201 virion is protected by an inner membrane, capsid, and outer membrane decorated by numerous transmembrane proteins. The virions are prone to deformation, and parts of their capsids deviate from the icosahedral arrangement. EhV-201 virions infect E. huxleyi by using their fivefold vertex to bind to a host cell and fuse the virus's inner membrane with the plasma membrane. Whereas the replication of EhV-201 probably occurs in the nucleus, virions assemble in the cytoplasm at the surface of endoplasmic reticulum-derived membrane segments. Genome packaging initiates synchronously with the capsid assembly and completes through an aperture in the forming capsid. Upon completion of genome packaging, the capsids change conformation, which enables them to acquire the outer membrane by budding into intracellular vesicles. EhV-201 infection induces the loss of surface protective layers from E. huxleyi cells, which allows the continuous release of virions by exocytosis. Our results provide insight into how EhVs bypass the surface protective layers of E. huxleyi and exploit the organelles of an infected cell for progeny assembly.
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