You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Introduction
============

Over the last two decades, multiple functions of microbiota have been investigated, from nutrition provision to reproduction ([@ref-38]; [@ref-23]; [@ref-2]). During the long-term associations, microbes have gone through genome decay and gene loss, resulting in tiny genomes ([@ref-23]). On one hand, protein-coding regions of these tiny genomes, which are easily accessible, have received broad attention. Considerable efforts have been made to elucidate the mechanisms underpinning the symbiosis by investigating protein-coding regions, and have yielded insights into the dynamics and functions of symbionts within the host ([@ref-45]). On the other hand, intergenic spacers (IGS) between protein-coding regions comprising of non-coding regions receive little attention. This situation has improved recently due to high-throughput sequencing method, which has allowed us to identify functional elements involved in gene regulation within IGSs ([@ref-6]; [@ref-10]). Questions concerning why microbiota choose to retain some regulatory elements in IGSs ([@ref-22]), are of particular interest.

The whitefly *Bemisia tabaci* is a genetically diverse group including multiple morphologically indistinguishable cryptic species ([@ref-5]). Among this species complex, two invasive species, Middle East-Asia Minor 1 (MEAM1, also known as B whitefly) and Mediterranean (MED, also known as Q whitefly), can cause severe damages to crops and plants around the world ([@ref-18]). There are also indigenous whitefly species, for instance, Asia II 3 and China 1 in China, causing less harm ([@ref-12]). The symbionts in whitefly are of vital importance, contributing to nutrient provision ([@ref-3]; [@ref-32]) and host fitness ([@ref-35]; [@ref-21]). *Portiera*, as the obligate symbiont, is uniformly harbored by all species of whiteflies ([@ref-41]). Studies on *Portiera* from the two invasive species of whiteflies MEAM1 and MED, have indicated that this bacterium mainly retains essential amino acid (EAA) biosynthesis genes ([@ref-31]; [@ref-37]; [@ref-13]). Besides, sequenced *Portiera* genomes contain around 30% IGSs, which is much higher than that of other obligate endosymbionts from insects ([@ref-36]; [@ref-25]). With such a largely reduced gene set and a high proportion of IGSs, compelling questions focusing on the regulatory capacities of *Portiera* arise. However, research on this issue has been restrained by various factors such as: (i) IGSs contain functional elements such as sRNAs and nonfunctional regions like decaying pseudogenes fragment, which limits their recognizability; (ii) *Portiera* in bacteriocytes is clustered with other secondary symbionts ([@ref-28]) and is hard to be isolated from insect tissues; (iii) *Portiera* cannot be cultured *in vitro*.

In this study, in order to obtain information about overall regulatory capacities in *Portiera* genomes, we first sequenced the *Portiera* genomes from two indigenous whitefly species (Asia II 3 and China 1). We then analyzed the gene sets of these two *Portiera* genomes, together with two other *Portiera* genomes derived previously from two other species of whiteflies, MEAM1 and MED, of the *B. tabaci* complex. By comparing four *Portiera* genomes, we: (i) screened the transcription-related genes by using OrthoMCL and BLASTP; (ii) demonstrated two σ^32^ binding sites experimentally; (iii) identified the functional elements located in IGSs using a phylogenetic foot-printing approach.

Materials & Methods
===================

Genome resources
----------------

Two *Portiera* genomes from two indigenous whitefly species (*B. tabaci* Asia II 3 and China 1) were sequenced and assembled according to a previously published protocol ([@ref-44]). Genome sequences of *Candidatus* Portiera aleyrodidarum from *B. tabaci* Asia II 3 and China 1 were submitted to the GenBank databases under accession numbers [CP016327](http://www.ncbi.nlm.nih.gov/nuccore/CP016327) and [CP016343](http://www.ncbi.nlm.nih.gov/nuccore/CP016343). Another three *Portiera* genome sequences (*Candidatus* Portiera aleyrodidarum BT-B, *Candidatus* Portiera aleyrodidarum BT-Q and *Candidatus* Portiera aleyrodidarum TV) were downloaded from National Center Biotechnology Information (NCBI), and the accession numbers were listed in [Table 1](#table-1){ref-type="table"}. In total, five *Portiera* genome sequences were analyzed and compared, with *Portiera*-B abbreviated for *Candidatus* Portiera aleyrodidarum from *B. tabaci* MEAM1 species, *Portiera*-Q for *Candidatus* Portiera aleyrodidarum of *B. tabaci* MED, *Portiera*-Z1 for *Candidatus* Portiera aleyrodidarum of *B. tabaci* Asia II 3, *Portiera*-Z3 for *Candidatus* Portiera aleyrodidarum of *B. tabaci* China 1 and *Portiera*-TV for *Candidatus* Portiera aleyrodidarum of greenhouse whitefly *Trialeurodes vaporariorum*.

10.7717/peerj.7477/table-1

###### General feature of five *Portiera* genomes.

![](peerj-07-7477-g005)

                                          ***Portiera*-Z1**                                          ***Portiera*-Z3**                                          ***Portiera*-B**                                           ***Portiera*-Q**                                           ***Porteira*-TV**
  --------------------------------------- ---------------------------------------------------------- ---------------------------------------------------------- ---------------------------------------------------------- ---------------------------------------------------------- ----------------------------------------------------------
  Genome size, bp                         354,523                                                    359,359                                                    358,242                                                    357,472                                                    280,663
  CDS number                              250                                                        247                                                        256                                                        255                                                        267
  Intergenic spacers, %                   32.9                                                       39.4                                                       33.5                                                       33.5                                                       7.7
  GC content, % (Protein-coding region)   26.7                                                       26.4                                                       26.7                                                       26.7                                                       24.4
  GC content, % (Intergenic spacers)      24.9                                                       25.6                                                       25.1                                                       24.9                                                       28.4
  Accession number                        [CP016327](http://www.ncbi.nlm.nih.gov/nuccore/CP016327)   [CP016343](http://www.ncbi.nlm.nih.gov/nuccore/CP016343)   [CP003708](http://www.ncbi.nlm.nih.gov/nuccore/CP003708)   [CP003835](http://www.ncbi.nlm.nih.gov/nuccore/CP003835)   [CP004358](http://www.ncbi.nlm.nih.gov/nuccore/CP004358)

Phylogenetic analysis
---------------------

Whitefly species phylogeny was determined first by using whitefly mitochondrial cytochrome oxidase I (COI) genes downloaded from NCBI database. The tree was built using MrBayes (v.3.4.2) ([@ref-30]), with the best-fitting model (TIM3 + G) generated by jModelTest ([@ref-4]). For *Portiera* phylogenetic analysis, *Candidatus* Portiera aleyrodidarum TV served as an out-group member according its host taxonomic system. To obtain the homologous genes among the five *Portiera* genomes, protein-coding regions were extracted from each genome and subjected to OrthoMCL ([@ref-15]) with default parameters for orthologs identification. A total of 218 genes were defined as core-genes among the five genomes. The protein sequences of core-genes were concatenated, and aligned using MUSCLE ([@ref-7]). The phylogeny was conducted by using Mrbayes, with the best-fitting model (cpREV + G + F) determined by ProtTest ([@ref-1]).

Recognization of transcription-related genes
--------------------------------------------

To focus on the *Portiera* from the whitefly *B. tabaci* only, 227 core-genes were determined by OrthoMCL among the four *Portiera* genomes from whitefly *B. tabaci*, and subjected to BLASTP (*E*-value \<10^−5^) and the Kyoto Encyclopedia of Genes and Genome (KEGG) Automatic Annotation Server tool ([@ref-24]) for functional prediction. *Escherichia coli* K12 (commonly used as a model organism) ([@ref-14]) served as a reference to predict transcription-related genes (mainly the amino acid biosynthetic pathways) and heat regulon within the protein-coding genes of *Portiera* genomes. *Ka/Ks* ratios between different gene pairs of *cspA* were calculated using DnaSP (v 5.10.1) ([@ref-17]). σ^32^ binding sites in the regulatory region of genes were determined based on consensus sequences of σ^32^ binding sites in *E. coli* (CTTGAAA \[11--15\] CCCCATnT) with the criteria previously described ([@ref-43]).

MED whitefly heat shock treatment
---------------------------------

Insects are ectotherms and they are not able to control body temperatures. Hence, the elevation of environmental temperature will influence the bacterial symbionts within whitefly. In order to investigate possible function of predicted σ^32^ binding sites, MED whiteflies were subjected to a high temperature of 40 °C for 3 h, 25 °C as control. This high temperature of 40 °C has been shown to cause thermal stress of whiteflies ([@ref-42]). Temperature exposure experiments were conducted in climatic chambers (Sanyo, MLR-350H; Sanyo Electric Co., Ltd., Osaka, Japan) which offered precise control of temperatures within ± 0.5 °C of the set value. Newly emerged whiteflies were placed in tubes (2.5 cm × 0.5 cm diam) covered with gauze, and then exposed to 40 °C and 25 °C (control) for 3 h.

DNA (lysis buffer method) ([@ref-8]) and RNA (TRIzol protocol) ([@ref-29]) were extracted from whitefly samples, four biological replicates for DNA and 4 for RNA, with each replicate containing five males and five females. RNA was then reverse transcribed into cDNA using PrimeScript RT reagent Kit (Takara, Japan) after RNase-free DNase I treatment. Both DNA and cDNA samples were then subjected to quantitative PCR (qPCR) according to manufacturer's instructions. The primers utilized were listed in [Table S1](#supp-1){ref-type="supplementary-material"}. The qPCR results were calculated using the comparative *C*~*T*~ method (2^−ΔΔ*CT*^). The 2^−ΔΔ*CT*^ method normalized the amount of target genes in each sample against whitefly nuclear gene encoding beta-Actin (DNA samples), and gene expression level of target genes against whitefly nuclear gene encoding the ribosomal protein L29 (RPL29) (cDNA samples) ([@ref-16]). The significance level was determined by using Student's *t*-test.

Functional elements searching in intergenic spacers
---------------------------------------------------

Orthologous IGSs were defined as sequences flanked by orthologous genes in genomes when comparing different genomes ([@ref-6]). IGSs from four *Portiera* genomes (from whitefly *B. tabaci*) were extracted and clustered in groups based on orthologous relationship. The lengths of paired orthologous IGSs were scattered to investigate the length variations between *Portiera* genomes from different species to examine their relationship. The orthologous IGSs were then aligned with MUSCLE. Identically aligned loci with more than 20 nucleotides in length were extracted and subjected to further analysis using a variety of means to investigate functional elements retained. Shine-Dalgarno sequences were predicted by RBSfinder ([@ref-39]), with default parameters. Putative small RNAs were selected by using RNAFold ([@ref-19]), only if the minimum free energy was below 0 kcal/mole.

These transcriptional elements were investigated in another three *Portiera* genomes available, *Portiera*-TV and two other *Portiera* genomes (from *Aleurodicus dispersus* and *Aleurodicus floccissimus*, NCBI accession number [LN649255](http://www.ncbi.nlm.nih.gov/nuccore/LN649255) and [LN734649](http://www.ncbi.nlm.nih.gov/nuccore/LN734649)). According to the orthologous IGSs containing the transcriptional elements in the *Portiera* genomes from *Bemisia tabaci*, sequences of the orthologous IGSs in the other three *Portiera* genomes (not from whitefly *Bemisia tabaci*) were extracted, and only sequences with a length over 20 nucleotides were kept. The investigation of transcriptional elements was performed as described previously.

Results and Discussion
======================

The genome of *Candidatus* Portiera aleyrodidarum BT-Z1 from whitefly Asia II 3 was 354,523 base pairs (bp) and contained 288 protein coding genes. For *Candidatus* Portiera aleyrodidarum BT-Z3 from whitefly China 1, the genome size was 359,359 bp, with 291 protein-coding genes identified. Both *Portiera* genomes were AT-rich, with 33 tRNA-coding genes and three rRNA-coding genes (5S, 16S and 23S). Together with *Portiera*-B from the whitefly MEAM1 and *Portiera*-Q from the whitefly MED, *Portiera* genomes in these four species of whiteflies (*Bemisia tabaci*) showed higher (than *Portiera* genome from whitefly *Trialeurodes vaporariorum*) similarity in genome size, coding sequence number and GC content ([Table 1](#table-1){ref-type="table"}).

The divergence and function of Portiera
---------------------------------------

In order to determine the phylogeny of *Portiera* in whitefly species, 218 orthologs among five *Portiera* genomes were generated, including four *Portiera* genomes from *B. tabaci* whitefly species and the *Portiera* genome from the greenhouse whitefly *T. vaporariorum* (as an out-group member). Sequence similarities between different *Portiera* pairs were calculated ([Table S2](#supp-2){ref-type="supplementary-material"}). Interestingly, *Portiera*-B and -Q from invasive whitefly species showed the highest similarity (99.8%), and meanwhile, *Portiera*-Z1 and Z3 also present strong similarity (99.5%). However, the similarity of *Portiera* genomes between *B. tabaci* whitefly and greenhouse whitefly was only about 77%. The classification of *Portiera* was also evidenced by the phylogenetic tree, where four *Portiera* genomes from *B. tabaci* obviously formed two different clades, in coincidence with the classification of whitefly *B. tabaci* species ([Fig. 1](#fig-1){ref-type="fig"}). Previous study on the divergence of whiteflies has implied that the divergence of the greenhouse whitefly *T. vaporariorum* and whitefly *B. tabaci* is dated back to 85.95 Ma, while the divergence of the species of whitefly *B. tabaci* is quite recent, approximately 17.73 Ma ([@ref-33]). We believe that long-term co-existence within respective whitefly species following the divergence of whiteflies, probably contributes to the differences of *Portiera* genomes. Meanwhile, it is also revealed that although *B. tabaci* lineage (*Portiera* genomes from whitefly *B. tabaci*) is evolving faster than other lineages, the diversity among the *B. tabaci* lineage is smaller when compared to other lineages ([@ref-33]). Our results on the similarity ([Table S2](#supp-2){ref-type="supplementary-material"}) and phylogeny ([Fig. 1](#fig-1){ref-type="fig"}) are in accordance with this finding.

![Bayes trees showing the phylogeny of *Portiera* and whitefly gene *mitochondrial cytochrome oxidase I* (*COI*) from five whitefly species.\
*Portiera* analysis was based on 218 core-genes determined by OrthoMCL. *Portiera* genome and *COI* gene from *Trialeurodes vaporariorum* served as out-group members, respectively. Posterior probabilities are given on the nodes.](peerj-07-7477-g001){#fig-1}

Despite the differences, from the orthologs and KEGG pathway analysis, two *Portiera* genomes from indigenous whitefly species in this study kept an identical set of genes dedicated to EAA biosynthesis and metabolisms ([Fig. 2](#fig-2){ref-type="fig"}), indicating that *Portiera* in indigenous whitefly species may also be responsible for EAA provision. Meanwhile, *Portiera*-TV and two other *Portiera* genomes (from *Aleurodicus dispersus* and *Aleurodicus floccissimus*, NCBI accession numbers [LN649255](http://www.ncbi.nlm.nih.gov/nuccore/LN649255) and [LN734649](http://www.ncbi.nlm.nih.gov/nuccore/LN734649)) are all predicted to contain the ability in amino acid biosynthesis ([@ref-33]). Our results provided further evidence that *Portiera* enters into whitefly before the divergence, and is conserved as an essential part of whitefly genome, contributing to EAA provision.

![Genes involved in amino acids biosynthesis pathways present in four *Portiera* genomes.\
The blue rectangle indicates that the gene is present in the genome.](peerj-07-7477-g002){#fig-2}

Genes related with transcription
--------------------------------

To generate and compare a putative set of genes globally retained by *Portiera* from *B. tabaci*, 227 orthologous genes were determined from four *Portiera* genomes of whitefly *B. tabaci*. Regulatory genes related with amino acid biosynthetic pathways were all missing compared to *E. coli* ([Table S3](#supp-3){ref-type="supplementary-material"}). The only transcription factor found in *Portiera* was gene *cspA*, which encodes a major cold-shock protein in *E. coli* ([@ref-34]). Besides, purifying selection was found acting on this gene ([Table S4](#supp-4){ref-type="supplementary-material"}).

The lack of EAA regulation genes means a crippled ability of *Portiera* to regulate the biosynthesis of EAA. On the other hand, it has been pointed out that the genome of whitefly contains several genes that are within EAAs biosynthetic pathways ([@ref-20]). Hence, those genes from whitefly genome, other than genes from *Portiera* genomes, are supposed to be possible candidates that regulate biosynthesis pathways of EAAs.

In addition, some other common regulatory elements were detected. Three genes (*nusA, nusG* and *rho*) involved in *transcriptional termination were present, indicating that the* termination of transcription in *Portiera* may fall into both intrinsic termination and *rho*-dependent termination ([@ref-27]). Core RNA polymerase (α~2~ββ′) was supposed to be complete, with the presence of *rpoA*, *rpoB*, and *rpoC*, which encodes α, β, and β′ subunit. RNA polymerase (RNAP) is of transcriptional importance in bacteria. Two σ factors functioning in the RNAP recognition of promoter sequences, were also suggested by the *Portiera* genomes. Along with primary σ factor σ^70^ (encoded by *rpoD*), σ^32^ (encoded by *rpoH*) was also detected, which is similar to *E. coli* ([@ref-11]) and *Buchnera* in aphids ([@ref-43]). Generally, this σ^32^ factor can compete with σ^70^, when the bacterium is confronted with heat stress, to redirect RNAP to promoters which contain σ^32^ binding sites.

Heat shock treatment
--------------------

The detection of σ^32^ factor led to a set of 14 genes retained in *Portiera* as heat shock regulon, according to heat shock regulon of *E. coli* ([@ref-26]) ([Table 2](#table-2){ref-type="table"}). These genes are predicted to encode relevant proteins responsible for cellular homeostasis, which indicates that heat shock response is probably partially conserved in *Portiera.* Meanwhile, promoter loci of the 14 genes were screened, with two possible σ^32^ binding sites detected ([Fig. 3](#fig-3){ref-type="fig"}). Intriguingly, the σ^32^ binding sites were conserved among 4 *Portiera* genomes in whitefly *B. tabaci*, with identical −35 and −10 loci. Additionally, in *E. coli* and *Buchnera* genomes from aphids, σ^32^ binding sites are also found before genes *grpE* and *dnaKJ* (respectively), suggesting a possible universal mechanism of conserving σ^32^ recognition sequences before these three genes ([@ref-43]).

10.7717/peerj.7477/table-2

###### Expression level variation of heat shock regulon from *Portiera*.

The dynamics (FoldChange, FC) were determined by quantitative real-time PCR analysis of gene expression under heat shock (40 °C) and normal temperature (25 °C). Significance level was determined by using *t*-test.

![](peerj-07-7477-g006)

  Genes                                      Log2FC   FC (MEAN ± S.E.M.)   *p*-value
  ------------------------------------------ -------- -------------------- ----------------------------------------
  *groES*[^b^](#table-2fn5){ref-type="fn"}   2.96     7.79 ± 1.949         [^\*^](#table-2fn1){ref-type="fn"}
  *dnaK*[^a^](#table-2fn4){ref-type="fn"}    2.66     6.31 ± 0.868         [^\*\*\*^](#table-2fn3){ref-type="fn"}
  *ftsH*                                     2.64     6.24 ± 0.809         [^\*\*\*^](#table-2fn3){ref-type="fn"}
  *dnaJ*[^a^](#table-2fn4){ref-type="fn"}    2.42     5.34 ± 1.174         [^\*^](#table-2fn1){ref-type="fn"}
  *grpE*[^a^](#table-2fn4){ref-type="fn"}    2.26     4.79 ± 1.606         [^\*^](#table-2fn1){ref-type="fn"}
  *hslV*                                     2.04     4.12 ± 0.642         [^\*\*^](#table-2fn2){ref-type="fn"}
  *lon*                                      1.74     3.33 ± 0.523         [^\*\*^](#table-2fn2){ref-type="fn"}
  *ybeY*                                     1.67     3.18 ± 0.773         [^\*^](#table-2fn1){ref-type="fn"}
  *groEL*[^b^](#table-2fn5){ref-type="fn"}   1.65     3.14 ± 0.347         [^\*\*^](#table-2fn2){ref-type="fn"}
  *ileS*                                     1.55     2.92 ± 0.383         [^\*\*^](#table-2fn2){ref-type="fn"}
  *rpoH* (*σ*^32^ factor)                    1.54     2.91 ± 0.325         [^\*\*^](#table-2fn2){ref-type="fn"}
  *valS*                                     1.46     2.75 ± 0.237         [^\*\*\*^](#table-2fn3){ref-type="fn"}
  *hslU*                                     1.39     2.61 ± 0.393         [^\*\*^](#table-2fn2){ref-type="fn"}
  *rpoD*                                     1.22     2.33 ± 0.300         [^\*\*^](#table-2fn2){ref-type="fn"}
  *glnS*                                     0.94     1.92 ± 0.331         [^\*^](#table-2fn1){ref-type="fn"}

**Notes.**

For *p* \< 0.5.

For *p* \< 0.01.

For *p* \< 0.001.

Genes *dnaK*, *dnaJ* and *grpE* are predicted to be in the same operon, sharing the same *σ*^32^ binding site upstream of *grpE*.

Genes *groEL* and *groES* are predicted to be in the same operon, sharing the same *σ*^32^ binding site upstream of *groES*.

![*σ*^32^ binding sites conserved in seven *Portiera* genomes.\
Whitefly species indicates the origin of the *Portiera*. '*Bemisia tabaci*' contains four species of whitefly *Bemisia tabaci*. The *σ*^32^ binding sites were determined based on the consensus sequence of that in *Escherichia coli* with certain criteria. The grey shaded loci mean the same nucleotides as that in consensus sequence.](peerj-07-7477-g003){#fig-3}

To identify possible function and efficiency of σ^32^ binding sites, MED whiteflies were treated at two temperatures, 40 °C and 25 °C (as control) for 3 h, and collected immediately. qPCR was conducted on *Portiera* 16S rDNA to quantify the density of *Portiera*, and 14 predicted heat-related genes in MED whitefly (using cDNA) to determine the possible differential expression of them between the heat shock treatment samples and control samples. The density of *Portiera* didn't significantly increase after heat shock (control vs. heat shock treatment, 1.00 ± 0.114 vs. 1.27 ± 0.187, Mean ± Stand Error Mean, *t*-test, *p* = 0.259). However, all the 15 genes (including *rpoH* encoding σ^32^factor) tested present significant variations ([Table 2](#table-2){ref-type="table"}).

Our results of *Portiera* are quite similar to that of *Buchnera* ([@ref-43]), that only modest dynamics of gene expression are observed compared to free-living *E. coli*. This is probably due to the weakness of the σ^32^ promoters ([@ref-43]). On the other hand, we focused on six genes *dnaK*, *groEL*, *groES*, *ftsH*, *dnaJ* and *hslV*, with log2FoldChange \>2. The results suggested that genes with predicted σ^32^ binding sites showed higher upregulation under heat shock. One σ^32^ binding site was proposed in the promoter of *grpE*, *dnaK* and *dnaJ.* These three genes were conjunct to each other, and supposed to be in the same operon according to genomic data. This σ^32^ binding site containing promoter may control the transcription of the three genes. Meanwhile, genes *groEL* and *groES* may also be in the same operon and be regulated together, with the σ^32^ binding sites in the upstream of *groES*. However, *ftsH* and *hslV* did not have recognized σ^32^ binding sites in immediate upstream spacer regions. How the transcription of these two genes were induced remains unclear.

Furthermore, we investigated the σ^32^ binding sites in another three available *Portiera* genomes, which are from different whitefly species ([Fig. 3](#fig-3){ref-type="fig"}). The σ^32^ binding site upstream of *grpE* in 7 *Portiera* genomes showed weak similarities, while σ^32^ binding site close to *groES* presented an almost identical sequence. It is indicated that the regulation of *groES* and *groEL* might be universally kept in *Portiera* of whitefly (including whitefly *Bemisia tabaci*), and thermal tolerance ability may conserved among *Portiera* in different species of whiteflies.

Putative functional elements in intergenic spacers of *Portiera* genomes
------------------------------------------------------------------------

For intergenic spacers, we focused on *Portiera* genomes from whitefly *B. tabaci* species only. Intergenic spacers occupy over 30% of the *Portiera* genomes from whitefly *B. tabaci*, thus leading to the investigation for possible regulatory elements in intergenic spacers. Strong associations between lengths of orthologous IGSs were observed between four *Portiera* genomes ([Fig. 4](#fig-4){ref-type="fig"}), which suggests that four *Portiera* genomes are coherently arranged even in the non-coding region with only subtle variations, indicating genome stasis ([@ref-40]). Notably, there is a closer relationship between the two invasive species and between the two indigenous species, as evidenced by *r*^2^ values ([Fig. 4](#fig-4){ref-type="fig"}), which is in agreement with phylogeny ([Fig. 1](#fig-1){ref-type="fig"}).

![Length associations of orthologous IGSs between different pairs of *Portiera* genomes.\
(A) Comparison between Portiera-B and Portiera-Q; (B) comparison between Portiera-Z3 and Portiera-Q; and (C) comparison between Portiera-Z3 and Portiera-Z1.](peerj-07-7477-g004){#fig-4}

Those determined IGSs were then aligned among four *Portiera* from different whitefly species, which identified 95 IGSs ([Data S1](#supp-5){ref-type="supplementary-material"}) orthologous (over 20 nucleotides in length) ranging from 20 to approximately 4700 nucleotides. The conserved loci are quite AT-rich with GC contents only around 23.5%. Furthermore, identically aligned loci among four *Portiera* occupied only a total of 62,438 nt, about 52% of all the orthologous IGSs. The stretch of identically aligned loci was probably interrupted by decayed pseudogenes at varying stages or random mutations in some preserved functional elements. Notably, 51 loci ([Data S1](#supp-5){ref-type="supplementary-material"}) were over 20 nucleotides in length and were subjected to further analysis. In all, 37 perfectly conserved or nearly perfectly conserved Shine-Dalgarno sequences ([Data S1](#supp-5){ref-type="supplementary-material"}) were detected (consensus sequence AGGAG), as well as 34 putative small RNAs predicted ([Data S1](#supp-5){ref-type="supplementary-material"}) by using RNAFold. Since functional elements tend to evolve slower than nonfunctional elements ([@ref-9]), the predicted functional loci within IGSs may be involved in the process of transcriptional regulation. The predicted loci need further study for a better understanding of transcriptional regulation within the non-coding region.

Meanwhile, these predicted transcriptional elements were searched against another three *Portiera* genomes available, *Portiera*-TV, and *Portiera* genomes from *A. dispersus* and *A. floccissimus*. Among the 37 Shine-Dalgarno sequences detected in *Portiera* genomes of whitefly, eight of them were also detected in the orthologous IGSs from the additional three *Portiera* genomes, with another three Shine-Dalgarno sequences detected only in one or two additional *Portiera* genomes. Moreover, according to the 34 orthologous IGSs containing putative small RNAs in *Portiera* genomes of whitefly *B. tabaci*, corresponding regions in the extra three *Portiera* genomes were extracted, resulting in 22 orthologous IGS groups ([Data S1](#supp-5){ref-type="supplementary-material"}). Each group contains at least one orthologous IGSs sequence from another three *Portiera* genomes. Interestingly, there were 11 groups, in which seven sequences were predicted to contain a putative small RNA, meaning these sRNAs were universally kept by *Portiera* genomes investigated, and within the orthologous IGS regions. Previous prediction on the divergence of whitefly species, wherein the separation between *Portiera* strains from *A. dispersus* and *A. floccissimus*, and *T. vaporariorum* and *B. tabaci*, was around 129 Ma, implies that the conserved elements found here might have been conserved at least 129 million years. However, the functions of these sRNAs need further investigation.

Conclusions
===========

Taken as a whole, our study indicates similar function of *Portiera* in whitefly *B. tabaci* and the first to investigate putative transcriptional regulation processes in *Portiera* of whitefly *B. tabaci*. Several regulatory elements in both coding and non-coding regions are revealed, by the combination of orthologous and phylogenetic footprinting approaches. For the coding regions, four *Portiera* genomes retained a similar set of genes that are responsible for transcriptional regulation. In particular, the possible thermal tolerance ability of *Portiera* was revealed genetically and experimentally. Although non-coding regions contain decayed pseudogenes, *Portiera* genomes of whitefly *B. tabaci* still retain functional elements including putative sRNAs. This finding demonstrates regulation within symbiont genomes and gives insights into symbiosis mechanisms.

Supplemental Information
========================

10.7717/peerj.7477/supp-1

###### Primers utilized in quantitative PCR

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Click here for additional data file.

10.7717/peerj.7477/supp-2

###### Sequence similarities (%) between different *Portiera* species pairs

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Click here for additional data file.

10.7717/peerj.7477/supp-3

###### No retention of regulatory genes for essential amino acid biosynthesis pathways in *Portiera* inferred from *Escherichia coli*

###### 

Click here for additional data file.

10.7717/peerj.7477/supp-4

###### Calculation of *Ka/Ks* ratio of genes *cspA* between orthologous pairs from different *Portiera* species

###### 

Click here for additional data file.

10.7717/peerj.7477/supp-5

###### List of 95 intergenic spacers (IGS) orthologs, 51 perfectly aligned IGS (over 20 nucleotides), 37 Shine-Dalgarno sequences and 34 putative small RNAs

###### 

Click here for additional data file.

We thank Professor Shu-Sheng Liu of Zhejiang University and Melissa J. Ishler of Pennsylvania State University for their comments and suggestions in the preparation of the manuscript.

Additional Information and Declarations
=======================================

The authors declare there are no competing interests.

[Dan-Tong Zhu](#author-1){ref-type="contrib"} conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper.

[Chi Zou](#author-2){ref-type="contrib"} and [Fei-Xue Ban](#author-3){ref-type="contrib"} performed the experiments.

[Hua-Ling Wang](#author-4){ref-type="contrib"} prepared figures and/or tables, authored or reviewed drafts of the paper.

[Xiao-Wei Wang](#author-5){ref-type="contrib"} conceived and designed the experiments, contributed reagents/materials/analysis tools.

[Yin-Quan Liu](#author-6){ref-type="contrib"} conceived and designed the experiments, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

The following information was supplied regarding data availability:

The sequences of Portiera from whitefly B. tabaci Asia II 3 (previously referred to as ZHJ1 'biotype') (Portiera BT-Z1) and Portiera from whitefly *B. tabaci* China 1 (previously referred to as ZHJ3 'biotype') (Portiera BT-Z3) are available in GenBank under accession numbers [CP016327](http://www.ncbi.nlm.nih.gov/nuccore/CP016327) and [CP016343](http://www.ncbi.nlm.nih.gov/nuccore/CP016343).