Runjia Ji’s research while affiliated with Planetary Science Institute and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (5)


Biomineralization in magnetotactic bacteria: From diversity to molecular discovery-based applications
  • Literature Review
  • Full-text available

November 2024

·

92 Reads

·

1 Citation

Cell Reports

Juan Wan

·

Runjia Ji

·

·

[...]

·

Download

The pipeline developed in this study. For the target-specific cell sorting and mini-metagenomics, different numbers of magnetotactic bacteria (MTB) cells were sorted with a micromanipulation system (Step 1), which were then lysed and used as the template of whole genome amplification (Step 2). After sequencing, assembly, and binning, the draft genome of the MTB population was obtained (Step 3). Genome annotation and subsequent analysis (including phylogeny analysis, metabolism analysis) were then performed (Step 4). For the NanoSIMS-based isotopic analysis, the stable-isotope incubated MTB cells were first magnetically enriched (Step 1), then characterized by fluorescence in situ hybridization (FISH) (Step 2) and focused ion beam scanning electron microscope (FIB-SEM) (Step 3), and finally analyzed by NanoSIMS at the single-cell level (Step 4)
Morphological and 16S rRNA gene-based phylogenetic identification of two kinds of MTB. a Light microscopy image of MTB cells at the edge of a water droplet. The blue arrowhead indicates the slow-moving large rod-shaped MTB (LHC-1), and the orange arrowhead indicates the spherical-shaped fast-moving small magnetotactic cocci (LHC-2). b and c TEM images of a LHC-1 cell (b) and a LHC-2 cell (c). Insets of b and c: magnification of the magnetosomes in black dashed rectangles. d Crystal length distribution of LHC-1 and LHC-2 cells. e Shape factor (width/length ratio) of crystals in LHC-1 and LHC-2 cells. Each blue (LHC-1) and orange (LHC-2) dot represents one magnetosome. n = 320 (LHC-1) and 69 (LHC-2) in d and e, respectively. f Phylogenetic positions of OTU1 (LHC-1) and OTU2 (LHC-2) based on 16S rRNA gene sequences. Thirty-three previously published MTB 16S rRNA genes were used to construct the phylogenetic tree. The maximum likelihood phylogenetic tree was constructed using the MEGA v11.0.13 under the maximum composite likelihood model with the bootstrap value set to 1000. The bootstrap values of each node are indicated. Phyla names are illustrated on the right side of the figure. Besides, class names of phylum Pseudomonadota (previously known as Proteobacteria) were also illustrated, including η-proteobacteria (Magnetococcia according to the GTDB taxonomy), α-proteobacteria, and γ-proteobacteria. Branches belonging to different taxa are colored according to the names of different taxa
Genome-based taxonomic characterization of LHC-1. a Phylogenomic tree of Nitrospirota bacterial genomes including LHC-1, 41 MTB genomes, and 159 non-MTB genomes. The maximum-likelihood tree was constructed using IQ-TREE (v2.0.3) [53] under the LG+F+I+G4 substitution model based on the concatenated alignment of 120 single-copy marker proteins [51] generated with GTDB-Tk (v2.1.0) [52]. Nodes with bootstrap values larger than 75% are indicated with dots. Previously published MTB genomes were colored blue, while LHC-1 was colored red and indicated with a red triangle. The five classes (based on the GTDB taxonomy) under Nitrospirota were illustrated on the figure, and branches of each class are colored accordingly. b Heatmap of pairwise ANI values among all 42 Nitrospirota MTB genomes. Pairwise ANI was analyzed using FastANI (v1.1) [54] and visualized using pairwise ANI viz. (v1.0) (a Python package we developed in this study). Note that the classification analysis result from GTDB-Tk was integrated in the figure, and MTB genomes belonging to different genera were indicated using different colored bars and squares. LHC-1 and three previously published MTB genomes (DC0425bin1, XYR, and nDC0425bin1), which belong to the same species according to the ANI threshold of 95% [60], were highlighted in red
Schematic representation of MGCs in LHC-1 and previously reported representative Nitrospirota MTB. At least one representative MTB population from each genus within the Nitrospirota phylum was selected for comparison. Note that LHC-1 has a close phylogenetic relationship with populations of XYR and Mcas, which all belong to the same genus Magnetobacterium. The conserved magnetosome genes in Nitrospirota MTB are highlighted in light yellow boxes
The metabolic cartoon constructed from the LHC-1 genome. The overall metabolic potential of LHC-1 was analyzed using METABOLIC (v4.0) [44], and the key enzymes that related to carbon, nitrogen, and sulfur metabolic pathways were double checked using KofamScan (v1.3.0) [71] against KOfam database. The draft genome of LHC-1 possesses a nearly complete Wood-Ljungdahl (WL) pathway, most enzymes for the reductive tricarboxylic acid (rTCA) cycle, and a complete denitrification pathway and dissimilatory nitrate reduction to ammonium pathway. The draft genome of LHC-1 also possesses a set of genes involving sulfur cycling, ion transportation, riboflavin biosynthesis, and chemotaxis. The black solid arrows indicate the presence of related enzyme genes in the draft genome of LHC-1. The black dashed arrows indicate the related enzyme genes are not discovered in the genome. The magenta dashed arrows indicate the predicted events that have not been confirmed or analyzed

+3

Linking morphology, genome, and metabolic activity of uncultured magnetotactic Nitrospirota at the single-cell level

August 2024

·

86 Reads

·

1 Citation

Background Magnetotactic bacteria (MTB) are a unique group of microorganisms that sense and navigate through the geomagnetic field by biomineralizing magnetic nanoparticles. MTB from the phylum Nitrospirota (previously known as Nitrospirae) thrive in diverse aquatic ecosystems. They are of great interest due to their production of hundreds of magnetite (Fe3O4) magnetosome nanoparticles per cell, which far exceeds that of other MTB. The morphological, phylogenetic, and genomic diversity of Nitrospirota MTB have been extensively studied. However, the metabolism and ecophysiology of Nitrospirota MTB are largely unknown due to the lack of cultivation techniques. Methods Here, we established a method to link the morphological, genomic, and metabolic investigations of an uncultured Nitrospirota MTB population (named LHC-1) at the single-cell level using nanoscale secondary-ion mass spectrometry (NanoSIMS) in combination with rRNA-based in situ hybridization and target-specific mini-metagenomics. Results We magnetically separated LHC-1 from a freshwater lake and reconstructed the draft genome of LHC-1 using genome-resolved mini-metagenomics. We found that 10 LHC-1 cells were sufficient as a template to obtain a high-quality draft genome. Genomic analysis revealed that LHC-1 has the potential for CO2 fixation and NO3⁻ reduction, which was further characterized at the single-cell level by combining stable-isotope incubations and NanoSIMS analyses over time. Additionally, the NanoSIMS results revealed specific element distributions in LHC-1, and that the heterogeneity of CO2 and NO3⁻ metabolisms among different LHC-1 cells increased with incubation time. Conclusions To our knowledge, this study provides the first metabolic measurements of individual Nitrospirota MTB cells to decipher their ecophysiological traits. The procedure constructed in this study provides a promising strategy to simultaneously investigate the morphology, genome, and ecophysiology of uncultured microbes in natural environments. 6gfJ7qtcG81szcFZGMmDYdVideo Abstract


The under-recognized dominance of magnetosome gene cluster-containing bacteria in oxygen-stratified freshwater ecosystems

April 2024

·

130 Reads

·

1 Citation

Magnetotactic bacteria (MTB) capable of magnetosome organelle biomineralization and magnetotaxis are widespread in chemically stratified aquatic environments. Conventionally, it has long been considered that the overall abundance of MTB in microbiota is not very high and that Magnetococcia is the most frequently identified and predominant MTB members. However, the diversity and distribution of MTB in chemically stratified environments remain elusive due to the lack of large-scale systematic analyses. Here we conduct a comprehensive survey of genomes containing magnetosome gene clusters (MGCs), a group of genes responsible for magnetosome biomineralization and magnetotaxis, in 267 metagenomes from 38 oxygen-stratified freshwater environments. A total of 63 MGC-containing genomes belonging to eight bacterial phyla are reconstructed, including the newly identified Myxococcota. We discover an unexpectedly high relative abundance of putative MTB (up to 15.4% of metagenomic reads) in hypoxic and anoxic water columns, in which Deltaproteobacteria, rather than traditionally considered Magnetococcia, are the most ubiquitous and predominant MGC-containing bacteria. Our analysis reveals a depth-specific taxonomy and function of MGC-containing bacteria in stratified water columns shaped by physicochemical conditions. These findings underscore the unrecognized ecophysiological importance of MTB in freshwater ecosystems.


FIG 1 Overview of the MagCluster workflow. (a) Genomes are annotated using Prokka with a mandatory reference file of magnetosome proteins via --proteins. (b) Putative MGCs or MGC-containing contigs are retrieved by the MGC_Screen module from GenBank files generated by the annotation module. First, contigs are filtered by the contig length (--contiglength) and the minimum number of magnetosome genes in a contig (--threshold). Then, the length of a genomic region containing no less than the given number of magnetosome genes is checked to meet the value of --windowsize. Finally, contigs that pass all restrictions are regarded as putative MGC-containing contigs. (b1) Contigs shorter than 2,000 bp (by default) are discarded. (b2) Magnetosome genes are identified through a text-mining strategy using the keyword "magnetosome" in protein names, and contigs containing fewer than 3 (by default) magnetosome genes are discarded. (b3) Putative MGCs are screened under a 10,000-bp (by default) window, and the minimum number of magnetosome genes (3 by default) in each window size is rechecked. (c) Putative MGCs are compared and visualized using clinker. MAGs, metagenome-assembled genomes; SAGs, single amplified genomes.
MagCluster: a Tool for Identification, Annotation, and Visualization of Magnetosome Gene Clusters

January 2022

·

120 Reads

·

9 Citations

Microbiology Resource Announcements

Magnetosome gene clusters (MGCs), which are responsible for magnetosome biosynthesis and organization in magnetotactic bacteria (MTB), are the key to deciphering the mechanisms and evolutionary origin of magnetoreception, organelle biogenesis, and intracellular biomineralization in bacteria. Here, we report the development of MagCluster, a Python stand-alone tool for efficient exploration of MGCs from large-scale (meta)genomic data.


Two Metagenome-Assembled Genome Sequences of Magnetotactic Bacteria in the Order Magnetococcales

August 2020

·

149 Reads

·

5 Citations

Microbiology Resource Announcements

Magnetotactic bacteria represent a valuable model system for the study of microbial biomineralization and magnetotaxis. Here, we report two metagenome-assembled genome sequences of uncultivated magnetotactic bacteria belonging to the order Magnetococcales . These genomes contain nearly complete magnetosome gene clusters responsible for magnetosome biomineralization.

Citations (4)


... 8,[37][38][39][40][41] Together, the widespread distribution and high abundance of MTB emphasize their remarkable adaptability and their crucial ecological roles, such as geochemical cycling of C, N, and Fe. 42,43 How magnetosomes contribute to MTB survival in different extreme environments is an interesting avenue for future research. ...

Reference:

Biomineralization in magnetotactic bacteria: From diversity to molecular discovery-based applications
Linking morphology, genome, and metabolic activity of uncultured magnetotactic Nitrospirota at the single-cell level

... 27,35 Recent large-scale metagenomic investigations indicate that the relative abundance of MTB within the hypoxic and anoxic freshwater area can be quite high (up to 15.4% of metagenomic reads). 36 Deltaproteobacteria, rather than the traditionally considered Magnetococcia (Candidatus Etaproteobacteria), have been identified as the most ubiquitous and predominant MGC-containing bacteria in freshwater columns. 36 Furthermore, MTB can thrive in extreme aquatic environments, including extreme temperatures, pH, salinity, and pressure. ...

The under-recognized dominance of magnetosome gene cluster-containing bacteria in oxygen-stratified freshwater ecosystems

... 32 Overall, MTB have been discovered across at least 17 bacterial phyla (Figure 1), highlighting their remarkable phylogenetic diversity. Recently, several standalone tools, such as FeGenie 33 and MagCluster, 34 have been developed to efficiently explore MGCs from large-scale (meta) genomic datasets, further facilitating the discovery of new MTB species. ...

MagCluster: a Tool for Identification, Annotation, and Visualization of Magnetosome Gene Clusters

Microbiology Resource Announcements

... To obtain sufficient DNA for metagenomic sequencing, whole-genome amplification was carried out using the multiple displacement amplification technique with the Genomiphi V2 DNA Amplification Kit (GE Healthcare, United States). This approach has been widely used previously in various works (Kolinko et al., 2015;Monteil et al., 2019;Zhang et al., 2020b). The amplified DNA was purified by sodium acetate precipitation. ...

Two Metagenome-Assembled Genome Sequences of Magnetotactic Bacteria in the Order Magnetococcales

Microbiology Resource Announcements