Draft Genome Sequences of 6 Actinobacterial Strains Isolated from Rock Surfaces Obtained from Indian Stone Ruins in Tamil Nadu, India, and Rocks from New England, United States

Here, we report the draft genome sequences obtained for 6 actinobacterial strains isolated from stone surfaces acquired from New England and Indian ruins. These strains were sequenced to determine their potential functional roles in the stone microbiome. The strains belong to the genera Allobranchiibius, Agrococcus, Dermococcus, Leifsonia, and Mycobacterium

Genome sequence and comparative analysis of a putative entomopathogenic Serratia isolated from Caenorhabditis briggsae

Background: Entomopathogenic associations between nematodes in the genera Steinernema and Heterorhabdus with their cognate bacteria from the bacterial genera Xenorhabdus and Photorhabdus, respectively, are extensively studied for their potential as biological control agents against invasive insect species. These two highly coevolved associations were results of convergent evolution. Given the natural abundance of bacteria, nematodes and insects, it is surprising that only these two associations with no intermediate forms are widely studied in the entomopathogenic context. Discovering analogous systems involving novel bacterial and nematode species would shed light on the evolutionary processes involved in the transition from free living organisms to obligatory partners in entomopathogenicity. Results: We report the complete genome sequence of a new member of the enterobacterial genus Serratia that forms a putative entomopathogenic complex with Caenorhabditis briggsae. Analysis of the 5.04 MB chromosomal genome predicts 4599 protein coding genes, seven sets of ribosomal RNA genes, 84 tRNA genes and a 64.8 KB plasmid encoding 74 genes. Comparative genomic analysis with three of the previously sequenced Serratia species, S. marcescens DB11 and S. proteamaculans 568, and Serratia sp. AS12, revealed that these four representatives of the genus share a core set of ~3100 genes and extensive structural conservation. The newly identified species shares a more recent common ancestor with S. marcescens with 99 % sequence identity in rDNA sequence and orthology across 85.6 % of predicted genes. Of the 39 genes/operons implicated in the virulence, symbiosis, recolonization, immune evasion and bioconversion, 21 (53.8 %) were present in Serratia while 33 (84.6 %) and 35 (89 %) were present in Xenorhabdus and Photorhabdus EPN bacteria respectively. Conclusion: The majority of unique sequences in Serratia sp. SCBI (South African Caenorhabditis briggsae Isolate) are found in ~29 genomic islands of 5 to 65 genes and are enriched in putative functions that are biologically relevant to an entomopathogenic lifestyle, including non-ribosomal peptide synthetases, bacteriocins, fimbrial biogenesis, ushering proteins, toxins, secondary metabolite secretion and multiple drug resistance/efflux systems. By revealing the early stages of adaptation to this lifestyle, the Serratia sp. SCBI genome underscores the fact that in EPN formation the composite end result – killing, bioconversion, cadaver protection and recolonization- can be achieved by dissimilar mechanisms. This genome sequence will enable further study of the evolution of entomopathogenic nematode-bacteria complexes

PYOMELANIN IS PRODUCED BY SHEWANELLA ALGAE BRY AND EFFECTED BY EXOGENOUS IRON

Melanin production by S. algae BrY occurred during late/post-exponential growth in lactate-basal-salts liquid medium supplemented with tyrosine or phenylalanine. The antioxidant ascorbate inhibited melanin production, but not production of the melanin precursor, homogentisic acid. In the absence of ascorbate, melanin production was inhibited by the 4-hydroxyplenylpyruvate dioxygenase inhibitor, sulcotrione and Fe(II) (>0.2mM). These data support the hypothesis that pigment production by S. algae BrY was a result the conversion of tyrosine or phenylalanine to homogentisic acid which was excreted, auto-oxidized and self-polymerized to form pyomelanin. The inverse relationship between Fe(II) concentration and pyomelanin production has implications that pyomelanin may play a role in iron assimilation under Fe(II) limiting conditions

Time-resolved double-slit experiment with entangled photons

The double-slit experiment strikingly demonstrates the wave-particle duality of quantum objects. In this famous experiment, particles pass one-by-one through a pair of slits and are detected on a distant screen. A distinct wave-like pattern emerges after many discrete particle impacts as if each particle is passing through both slits and interfering with itself. While the direct event-by-event buildup of this interference pattern has been observed for massive particles such as electrons, neutrons, atoms and molecules, it has not yet been measured for massless particles like photons. Here we present a temporally- and spatially-resolved measurement of the double-slit interference pattern using single photons. We send single photons through a birefringent double-slit apparatus and use a linear array of single-photon detectors to observe the developing interference pattern. The analysis of the buildup allows us to compare quantum mechanics and the corpuscular model, which aims to explain the mystery of single-particle interference. Finally, we send one photon from an entangled pair through our double-slit setup and show the dependence of the resulting interference pattern on the twin photon's measured state. Our results provide new insight into the dynamics of the buildup process in the double-slit experiment, and can be used as a valuable resource in quantum information applications

Draft Genome Sequence of Frankia sp. Strain BCU110501, a Nitrogen-Fixing Actinobacterium Isolated from Nodules of Discaria trinevis

Frankia forms a nitrogen-fixing symbiosis with actinorhizal plants. We report a draft genome sequence for Frankia sp. strain BCU110501, a nitrogen-fixing actinobacterium isolated from nodules of Discaria trinevis grown in the Patagonia region of Argentina

Draft Genome Sequence of Frankia sp. Strain BMG5.12, a Nitrogen-Fixing Actinobacterium Isolated from Tunisian Soils

Members of the actinomycete genus Frankia form a nitrogen-fixing symbiosis with 8 different families of actinorhizal plants. We report a draft genome sequence for Frankia sp. strain BMG5.12, a nitrogen-fixing actinobacterium isolated from Tunisian soils with the ability to infect Elaeagnus angustifolia and Myrica gale

SOLUS: Multimodal System Combining Ultrasounds and Diffuse Optics for Tomographic Imaging of Breast Cancer

An innovative multimodal system for breast imaging was developed combining in a single probe B-mode ultrasound, shear-wave elastography and multi-wavelength time-domain diffuse optical tomography. The clinical validation is ongoing aiming at improving the diagnostic specificity

Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes

A machine learning classification algorithm is applied to the SOLUS database to discriminate benign and malignant breast lesions, based on absorption and composition properties retrieved through diffuse optical tomography. The Mann-Whitney test indicates oxy-hemoglobin (p-value = 0.0007) and lipids (0.0387) as the most significant constituents for lesion classification, but work is in progress for further analysis. Together with sensitivity (91%), specificity (75%) and the Area Under the ROC Curve (0.83), special metrics for imbalanced datasets (27% of malignant lesions) are applied to the machine learning outcome: balanced accuracy (83%) and Matthews Correlation Coefficient (0.65). The initial results underline the promising informative content of optical data

Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes

A machine learning classification algorithm is applied to the SOLUS database to discriminate benign and malignant breast lesions, based on absorption and composition properties retrieved through diffuse optical tomography. The Mann-Whitney test indicates oxy-hemoglobin (p-value = 0.0007) and lipids (0.0387) as the most significant constituents for lesion classification, but work is in progress for further analysis. Together with sensitivity (91%), specificity (75%) and the Area Under the ROC Curve (0.83), special metrics for imbalanced datasets (27% of malignant lesions) are applied to the machine learning outcome: balanced accuracy (83%) and Matthews Correlation Coefficient (0.65). The initial results underline the promising informative content of optical data