Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants

Background: Necrotizing enterocolitis (NEC) is a devastating intestinal disease that afflicts 10% of extremely preterm infants. The contribution of early intestinal colonization to NEC onset is not understood, and predictive biomarkers to guide prevention are lacking. We analyzed banked stool and urine samples collected prior to disease onset from infants 99% versus 99% versus 38% in the other NEC cases and 84% in controls, P = 0.01). NEC preceded by Firmicutes dysbiosis occurred earlier (onset, days 7 to 21) than NEC preceded by Proteobacteria dysbiosis (onset, days 19 to 39). All NEC cases lacked Propionibacterium and were preceded by either Firmicutes (≥98% relative abundance, days 4 to 9) or Proteobacteria (≥90% relative abundance, days 10 to 16) dysbiosis, while only 25% of controls had this phenotype (predictive value 88%, P = 0.001). Analysis of days 4 to 9 urine samples found no metabolites associated with all NEC cases, but alanine was positively associated with NEC cases that were preceded by Firmicutes dysbiosis (P < 0.001) and histidine was inversely associated with NEC cases preceded by Proteobacteria dysbiosis (P = 0.013). A high urinary alanine:histidine ratio was associated with microbial characteristics (P < 0.001) and provided good prediction of overall NEC (predictive value 78%, P = 0.007). Conclusions: Early dysbiosis is strongly involved in the pathobiology of NEC. These striking findings require validation in larger studies but indicate that early microbial and metabolomic signatures may provide highly predictive biomarkers of NEC

The relationship between genus richness and geographic area in Late Cretaceous marine biotas: epicontinental sea versus open-ocean-facing settings.

For present-day biotas, close relationships have been documented between the number of species in a given region and the area of the region. To date, however, there have been only limited studies of these relationships in the geologic record, particularly for ancient marine biotas. The recent development of large-scale marine paleontological databases, in conjunction with enhanced geographical mapping tools, now allow for their investigation. At the same time, there has been renewed interest in comparing the environmental and paleobiological properties of two broad-scale marine settings: epicontinental seas, broad expanses of shallow water covering continental areas, and open-ocean-facing settings, shallow shelves and coastlines that rim ocean basins. Recent studies indicate that spatial distributions of taxa and the kinetics of taxon origination and extinction may have differed in these two settings. Against this backdrop, we analyze regional Genus-Area Relationships (GARs) of Late Cretaceous marine invertebrates in epicontinental sea and open-ocean settings using data from the Paleobiology Database. We present a new method for assessing GARs that is particularly appropriate for fossil data when the geographic distribution of these data is patchy and uneven. Results demonstrate clear relationships between genus richness and area for regions worldwide, but indicate that as area increases, genus richness increases more per unit area in epicontinental seas than in open-ocean settings. This difference implies a greater degree of compositional heterogeneity as a function of geographic area in epicontinental sea settings, a finding that is consistent with the emerging understanding of physical differences in the nature of water masses between the two marine settings

Spatial protocol used in this study to build genus-area curves from fossil data.

<p>Blue dots represent fossil collections in the PaleoDB of marine invertebrates during the Cretaceous 6 time bin from the European Epicontinental sea. Inset: One collection was randomly chosen as a start point (yellow star); a convex hull was circumscribed around the start collection and the next two closest collections. Main figure: Each collection was added individually and a new convex hull was circumscribed around collections in order to calculate area. The rainbow lines represent a few convex hulls from this iteration. This process was then repeated using each collection as a start point.</p

Range of least-squares linear regression slopes for each region.

<p>Black dots represent actual slope values, while the colored lines represent the range in values for a given region. Solid lines represent values for analyses using PaleoDB temporal bins (Cretaceous 5–8); dotted lines represent slope values using stage divisions. White dots represent the stages within the Cretaceous 6 PaleoDB time bin: Turonian (T), Coniacian (C) and Santonian (S).</p

A comparison between least squares linear regression and LOESS regression.

<p>Least squares linear regression is displayed with dashed lines; LOESS by solid lines for (A) the European Epicontiental sea, (B) the North American Cretaceous interior seaway, and (C) the Gulf coast. LOESS was conducted with an alpha (smoothing parameter) of 0.4.</p

P-values for tests of significant differences between individual genus-area linear regression slopes.

<p>Comparison of regression lines was performed using ANCOVA, with a Bonferroni corrected alpha value of 0.0008. Regressions (shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040472#pone-0040472-g006" target="_blank">Fig. 6</a>) that are significantly different are bolded. Each regression is labeled by PaleoDB time bin, 5–8, and with an “E” for the European Epicontinental Sea, an “N” for the North American Cretaceous Interior Seaway or a “G” for the Gulf Coast.</p

PaleoDB collections from the Cretaceous 6 bin.

<p>The three regions examined: European Epicontinental Sea (orange), North American Cretaceous Seaway (yellow), and Gulf Coast (red). Map: Ron Blakey, NAU Geology <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040472#pone.0040472-Blakey1" target="_blank">[21]</a>.</p

Example of multiple genus-area relationship

<p>(<b>GAR</b>) <b>analyses plotted together.</b> Gray dots represent all iterations regionally; black dots represent the single iteration illustrated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040472#pone-0040472-g002" target="_blank">Fig. 2</a>. The colored dots correspond to the hulls pictured in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040472#pone-0040472-g002" target="_blank">Fig. 2</a>. Data are from the European Epicontinental Sea during the Cretaceous 6 time bin.</p

European Epicontinental Sea PaleoDB Collections.

<p>(A) Paleogeographic map of Europe (105Ma). Gray dots represent all PaleoDB collections from the European Epicontinental Sea used in full analyses; red dots represent collections used as a subset for the European Epicontinental Sea analysis. Map: Ron Blakey, NAU Geology <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040472#pone.0040472-Blakey1" target="_blank">[21]</a>. (B) Genus-Area plots with least-squares linear regression of subseted European Data.</p

Genus-Area Results.

<p>Genus-area (GAR) plots of the European Epicontinental Sea, the North American Cretaceous Interior Seaway and the Gulf Coast, an open-ocean-facing setting. Cretaceous 5–8 represent four ∼11 million year time bins spanning the Late Cretaceous (see text for discussion of time scale). Ordinary least-squares (black) and generalized least-squares (gray) linear regressions are also plotted. All slopes are highly significant, and each is significantly different from all others. Note: when it appears that only one regression line is present this is because the two lines coincide.</p